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  • 1.
    Pya Arnqvist, Natalya
    et al.
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för matematik och matematisk statistik.
    Sjöstedt de Luna, Sara
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för matematik och matematisk statistik.
    Abramowicz, Konrad
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för matematik och matematisk statistik.
    fiberLD: Fiber Length Determination. R package version 0.1-82024Övrigt (Övrigt vetenskapligt)
  • 2.
    Pya Arnqvist, Natalya
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för matematik och matematisk statistik.
    On some extensions of shape-constrained generalized additive modelling in R2024Manuskript (preprint) (Övrigt vetenskapligt)
    Abstract [en]

    Regression models that incorporate smooth functions of predictor variables to explain the relationships with a response variable have gained widespread usage and proved successful in various applications. By incorporating smooth functions of predictor variables, these models can capture complex relationships between the response and predictors while still allowing for interpretation of the results. In situations where the relationships between a response variable and predictors are explored, it is not uncommon to assume that these relationships adhere to certain shape constraints. Examples of such constraints include monotonicity and convexity. The scam package for R has become a popular package to carry out the full fitting of exponential family generalized additive modelling with shape restrictions on smooths. The paper aims to extend the existing framework of shape-constrained generalized additive models (SCAM) to accommodate smooth interactions of covariates, linear functionals of shape-constrained smooths and incorporation of residual autocorrelation. The methods described in this paper are implemented in the recent version of the package scam, available on the Comprehensive R Archive Network (CRAN).

  • 3.
    Pya Arnqvist, Natalya
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för matematik och matematisk statistik.
    scam: Shape constrained additive models. R package version 1.2-152024Övrigt (Övrigt vetenskapligt)
    Abstract [en]

    scam provides functions for generalized additive modelling under shape constraints on the component functions of the linear predictor of the GAM. Models can contain multiple shape constrained and unconstrained terms as well as bivariate smooths with double or single monotonicity.

  • 4.
    Abramowicz, Konrad
    et al.
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för matematik och matematisk statistik.
    Pini, Alessia
    Department of Statistical Sciences, Università Cattolica del Sacro Cuore, Milan, Italy.
    Schelin, Lina
    Umeå universitet, Samhällsvetenskapliga fakulteten, Handelshögskolan vid Umeå universitet, Statistik.
    Sjöstedt de Luna, Sara
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för matematik och matematisk statistik.
    Stamm, Aymeric
    Department of Mathematics Jean Leray, UMR CNRS 6629, Nantes University, Nantes, France.
    Vantini, Simone
    MOX – Modelling and Scientific Computing Laboratory, Department of Mathematics, Politecnico di Milano, Milan, Italy.
    Domain selection and family-wise error rate for functional data: a unified framework2023Ingår i: Biometrics, ISSN 0006-341X, E-ISSN 1541-0420, Vol. 79, nr 2, s. 1119-1132Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Functional data are smooth, often continuous, random curves, which can be seen as an extreme case of multivariate data with infinite dimensionality. Just as component-wise inference for multivariate data naturally performs feature selection, subset-wise inference for functional data performs domain selection. In this paper, we present a unified testing framework for domain selection on populations of functional data. In detail, p-values of hypothesis tests performed on point-wise evaluations of functional data are suitably adjusted for providing a control of the family-wise error rate (FWER) over a family of subsets of the domain. We show that several state-of-the-art domain selection methods fit within this framework and differ from each other by the choice of the family over which the control of the FWER is provided. In the existing literature, these families are always defined a priori. In this work, we also propose a novel approach, coined threshold-wise testing, in which the family of subsets is instead built in a data-driven fashion. The method seamlessly generalizes to multidimensional domains in contrast to methods based on a-priori defined families. We provide theoretical results with respect to consistency and control of the FWER for the methods within the unified framework. We illustrate the performance of the methods within the unified framework on simulated and real data examples, and compare their performance with other existing methods.

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  • 5.
    Shcherbak, Denys
    et al.
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för matematik och matematisk statistik.
    Pya Arnqvist, Natalya
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för matematik och matematisk statistik.
    Geometry on optimal problem2023Övrigt (Övrigt vetenskapligt)
    Abstract [en]

    We introduce an algorithm which can be directly used to feasible and optimum search in linear programming. Starting from an initial point the algorithm iteratively moves a point in a direction to resolve the violated constraints. At the same time, it ensures that previously fulfilled constraints are not breached during this process. The method is based on geometrical properties of n-dimensional space and can be used on any type of linear constraints (>, =, ≥), moreover it can be used when the feasible region is non-full-dimensional.

  • 6. Pataky, Todd Colin
    et al.
    Abramowicz, Konrad
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för matematik och matematisk statistik.
    Liebl, Dominik
    Pini, Alessia
    Sjöstedt de Luna, Sara
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för matematik och matematisk statistik.
    Schelin, Lina
    Umeå universitet, Samhällsvetenskapliga fakulteten, Handelshögskolan vid Umeå universitet, Statistik.
    Simultaneous inference for functional data in sports biomechanics: Comparing statistical parametric mapping with interval-wise testing2023Ingår i: AStA Advances in Statistical Analysis, ISSN 1863-8171, E-ISSN 1863-818X, Vol. 107, s. 369-392Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    The recent sports science literature conveys a growing interest in robust statistical methods to analyze smooth, regularly-sampled functional data. This paper focuses on the inferential problem of identifying the parts of a functional domain where two population means differ. We considered four approaches recently used in sports science: interval-wise testing (IWT), statistical parametric mapping (SPM), statistical nonparametric mapping (SnPM) and the Benjamini-Hochberg (BH) procedure for false discovery control. We applied these procedures to both six representative sports science datasets, and also to systematically varied simulated datasets which replicated ten signal- and/or noise-relevant parameters that were identified in the experimental datasets. We observed generally higher IWT and BH sensitivity for five of the six experimental datasets. BH was the most sensitive procedure in simulation, but also had relatively high false positive rates (generally > 0.1) which increased sharply (> 0.3) in certain extreme simulation scenarios including highly rough data. SPM and SnPM were more sensitive than IWT in simulation except for (1) high roughness, (2) high nonstationarity, and (3) highly nonuniform smoothness. These results suggest that the optimum procedure is both signal and noise-dependent. We conclude that: (1) BH is most sensitive but also susceptible to high false positive rates, (2) IWT, SPM and SnPM appear to have relatively inconsequential differences in terms of domain identification sensitivity, except in cases of extreme signal/noise characteristics, where IWT appears to be superior at identifying a greater portion of the true signal.

  • 7.
    Grinberg, Adam
    et al.
    Umeå universitet, Medicinska fakulteten, Institutionen för samhällsmedicin och rehabilitering, Avdelningen för fysioterapi.
    Strong, Andrew
    Umeå universitet, Medicinska fakulteten, Institutionen för samhällsmedicin och rehabilitering, Avdelningen för fysioterapi.
    Strandberg, Johan
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för matematik och matematisk statistik.
    Selling, Jonas
    Umeå universitet, Medicinska fakulteten, Institutionen för samhällsmedicin och rehabilitering, Avdelningen för fysioterapi.
    Liebermann, Dario G.
    Tel Aviv University, Tel Aviv, Israel.
    Björklund, Martin
    Umeå universitet, Medicinska fakulteten, Institutionen för samhällsmedicin och rehabilitering.
    Häger, Charlotte
    Umeå universitet, Medicinska fakulteten, Institutionen för samhällsmedicin och rehabilitering.
    An electroencephalography-based approach to evaluate movement-related anxiety in physically active adults and following anterior cruciate ligament injury2022Konferensbidrag (Refereegranskat)
    Abstract [en]

    Background: Psychophysiological consequences often persist following musculoskeletal trauma and can result in vastly decreased quality of life. Re-injury anxiety is particularly common among individuals following anterior cruciate ligament (ACL) injury. Existing assessments of re-injury anxiety are, however, restricted to subjective suboptimal questionnaires, which may result in under-reporting and thus poorer injury management. We propose a novel approach to objectively quantify arousal response to movement-related anxiety. A new experimental paradigm was implemented to induce and record a conditioned electrophysiological response to a sudden perturbation, experienced to be potentially injurious.

    Objective: To explore the feasibility of detecting anxiety-associated electrocortical response and to evaluate its discriminative ability between asymptomatic individuals and those who had experienced an ACL injury.

    Methods: Physically-active asymptomatic persons and individuals post-ACL reconstruction stood blindfolded on a perturbation platform capable of generating high-acceleration translations (1.5 m/s2). Auditory stimuli were repeatedly presented in four-second intervals, as either low- or high-frequency tones. Half of the high-frequency tones were followed 1.5 seconds later by a destabilizing perturbation in one of eight randomized directions. The two tone conditions were thus termed ‘Neutral’ and ‘Anxiety’, as the high-frequency tone was intended to invoke an arousal response in anticipation of a potential perturbation. Event-related potentials (ERP) were computed for nine electrodes by averaging 100 Neutral and 100 Anxiety trials. Significant ERP components were identified using functional data analysis. Paired difference-waves’ amplitudes (Neutral - Anxiety) were compared between groups.

    Results: ERP correlates of anxiety were detected for both groups in frontal and central midline locations, with an observable contingent negative variation (CNV) from 500 ms post-stimulus in Anxiety compared with Neutral trials. This ERP component is reflective of a threat-induced arousal response, associated with attention and expectancy of an anxiety-relevant event. Preliminary data indicate no group differences in CNV amplitudes.

    Conclusions: Objective evaluation of an arousal response to movement-related anxiety was found to be feasible, resulting in a threat-induced CNV. Further investigation will elucidate the discriminative power of such an approach to differentiate between individuals with high and low re-injury anxiety, as well as potential associations with existing patient-reported outcome measures.

  • 8.
    Pya Arnqvist, Natalya
    et al.
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för matematik och matematisk statistik.
    Arnqvist, Per
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för matematik och matematisk statistik.
    Sjöstedt de Luna, Sara
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för matematik och matematisk statistik.
    fdaMocca: Model-Based Clustering for Functional Data with Covariates. R package version 0.1-12022Övrigt (Övrigt vetenskapligt)
  • 9.
    Pya Arnqvist, Natalya
    et al.
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för matematik och matematisk statistik.
    Sjöstedt de Luna, Sara
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för matematik och matematisk statistik.
    Abramowicz, Konrad
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för matematik och matematisk statistik.
    fiberLD: Fiber Length Determination. R package version 0.1-72022Övrigt (Övrigt vetenskapligt)
  • 10.
    Abramowicz, Konrad
    et al.
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för matematik och matematisk statistik.
    Sjöstedt de Luna, Sara
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för matematik och matematisk statistik.
    Strandberg, Johan
    Umeå universitet, Samhällsvetenskapliga fakulteten, Handelshögskolan vid Umeå universitet, Statistik.
    Nonparametric bagging clustering methods to identify latent structures from a sequence of dependent categorical data2022Ingår i: Computational Statistics & Data Analysis, ISSN 0167-9473, E-ISSN 1872-7352, Vol. 177, artikel-id 107583Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Nonparametric bagging clustering methods are studied and compared to identify latent structures from a sequence of dependent categorical data observed along a one-dimensional (discrete) time domain. The frequency of the observed categories is assumed to be generated by a (slowly varying) latent signal, according to latent state-specific probability distributions. The bagging clustering methods use random tessellations (partitions) of the time domain and clustering of the category frequencies of the observed data in the tessellation cells to recover the latent signal, within a bagging framework. New and existing ways of generating the tessellations and clustering are discussed and combined into different bagging clustering methods. Edge tessellations and adaptive tessellations are the new proposed ways of forming partitions. Composite methods are also introduced, that are using (automated) decision rules based on entropy measures to choose among the proposed bagging clustering methods. The performance of all the methods is compared in a simulation study. From the simulation study it can be concluded that local and global entropy measures are powerful tools in improving the recovery of the latent signal, both via the adaptive tessellation strategies (local entropy) and in designing composite methods (global entropy). The composite methods are robust and overall improve performance, in particular the composite method using adaptive (edge) tessellations.

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  • 11.
    Pya Arnqvist, Natalya
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för matematik och matematisk statistik.
    scam: Shape constrained additive models. R package version 1.2-132022Övrigt (Övrigt vetenskapligt)
  • 12.
    Strandberg, Johan
    et al.
    Umeå universitet, Samhällsvetenskapliga fakulteten, Handelshögskolan vid Umeå universitet, Statistik.
    Sjöstedt de Luna, Sara
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för matematik och matematisk statistik.
    Mateu, Jorge
    University Jaume I of Castellon, Department of Mathematics, Spain.
    A comparison of spatiotemporal and functional kriging approaches2021Ingår i: Geostatistical functional data analysis / [ed] Mateu, Jorge: Giraldo, Ramón, John Wiley & Sons, 2021, s. 375-402Kapitel i bok, del av antologi (Refereegranskat)
    Abstract [en]

    Here we present and compare functional and spatiotemporal (Sp.T.) kriging approaches to predict spatial functional random processes, which can also be viewed as Sp.T. random processes. Comparisons are focused on Sp.T. kriging versus ordinary kriging for functional data (OKFD), since more flexible functional kriging approaches like pointwise functional kriging and functional kriging total model coincide with OKFD in several situations. Prediction performance is evaluated via functional cross-validation on simulated data as well as on a Canadian weather data set. The two kriging approaches perform in many cases rather equal for stationary Sp.T. processes. For nonstationary Sp.T. processes, OKFD performs better than Sp.T. kriging. The computational time for OKFD is considerably lower compared to those for the Sp.T. kriging methods.

  • 13.
    Strandberg, Johan
    et al.
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för matematik och matematisk statistik.
    Pini, Alessia
    Department of Statistical Sciences, Università Cattolica del Sacro Cuore, Milan, Italy.
    Häger, Charlotte
    Umeå universitet, Medicinska fakulteten, Institutionen för samhällsmedicin och rehabilitering, Avdelningen för fysioterapi.
    Schelin, Lina
    Umeå universitet, Samhällsvetenskapliga fakulteten, Handelshögskolan vid Umeå universitet, Statistik.
    Analysis Choices Impact Movement Evaluation: A Multi-Aspect Inferential Method Applied to Kinematic Curves of Vertical Hops in Knee-Injured and Asymptomatic Persons2021Ingår i: Frontiers in Bioengineering and Biotechnology, E-ISSN 2296-4185, Vol. 9, artikel-id 645014Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Three-dimensional human motion analysis provides in-depth understanding in order to optimize sports performance or rehabilitation following disease or injury. Recent developments of statistical methods for functional data allow for novel ways to analyze often complex biomechanical data. Even so, for such methods as well as for traditional well-established statistical methods, the interpretations of the results may be influenced by analysis choices made prior to the analysis. We evaluated the consequences of three such choices when comparing one-leg vertical hop (OLVH) performance in individuals who had ruptured their anterior cruciate ligament (ACL), to that of asymptomatic controls, and also athletes. Kinematic data were analyzed using a statistical approach for functional data, targeting entire curve data. This was done not only for one joint at a time but also for multiple lower limb joints and movement planes simultaneously using a multi-aspect methodology, testing for group differences while also accounting for covariates. We present the results of when an individual representative curve out of three available was either: (1) a mean curve (Mean), (2) a curve from the highest hop (Max), or (3) a curve describing the variability (Var), as a representation of performance stability. We also evaluated choice of sample leg comparison; e.g., ACL-injured leg compared to either the dominant or non-dominant leg of asymptomatic groups. Finally, we explored potential outcome effects of different combinations of included joints. There were slightly more pronounced group differences when using Mean compared to Max, while the specifics of the observed differences depended on the outcome variable. For Var there were less significant group differences. Generally, there were more disparities throughout the hop movement when comparing the injured leg to the dominant leg of controls, resulting in e.g., group differences for trunk and ankle kinematics, for both Mean and Max. When the injured leg was instead compared to the non-dominant leg of controls, there were trunk, hip and knee joint differences. For a more stringent comparison, we suggest considering to compare the injured leg to the non-dominant leg. Finally, the multiple-joint analyses were coherent with the single-joint analyses. The direct effects of analysis choices can be explored interactively by the reader in the Supplementary Material. To summarize, the choices definitively have an impact on the interpretation of a hop test results commonly used in rehabilitation following knee injuries. We therefore strongly recommend well-documented methodological analysis choices with regards to comparisons and representative values of the measures of interests.

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  • 14.
    Haemig, Paul D.
    et al.
    Nature Division, Government of Jönköping Province, Jönköping, Sweden; Department of Natural Sciences, Linneaus University, Kalmar, Sweden.
    Sjöstedt de Luna, Sara
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för matematik och matematisk statistik.
    Blank, Henrick
    Nature Division, Government of Jönköping Province, Jönköping, Sweden.
    Dynamic table-visiting behavior of birds at outdoor restaurants and cafés2021Ingår i: Ethology, ISSN 0179-1613, E-ISSN 1439-0310, Vol. 127, nr 7, s. 505-516Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Fear of humans and its effect on animal behavior is increasingly being recognized as an important structuring force in ecological landscapes, with consequences for ecological interactions and communities. When aggressive, physically dominant species are displaced by anthropogenic disturbance, physically weaker species exploit competitor and predator downtimes to forage in previously risky places. Birds feeding at outdoor restaurants and cafés in association with humans are exposed to fluctuating levels of perceived danger caused by frequently changing densities of human diners. Consequently, birds must make decisions about which dining tables to visit based on trade-offs between foraging gain and perceived danger from avian competitors and humans. We tested the hypothesis that interspecific differences in response to perceived danger, combined with varying densities of human diners, dynamically alter which bird species predominates at dining tables. We found that house sparrows (Passer domesticus) tolerated higher human diner-densities than larger-sized, more physically dominant Eurasian jackdaws (Coloeus monedula). Sparrows were usually the first birds to visit diner-occupied tables and spent more time there than jackdaws. However, at diner-abandoned tables, this pattern changed: During low diner-densities at surrounding tables, jackdaws were usually the predominant species in first visits and minutes spent visiting, while at high diner-densities sparrows usually predominated. Moreover, along a gradient of increasing human diner-density, sparrows gradually replaced jackdaws as the predominant species in first visits and time at abandoned tables. However, at diner-occupied tables, once a sparrow chose which table to visit, factors other than diner-density influenced its choice of where to forage there (table-top or ground). To our knowledge, our research is the first scientific study of table-visiting behavior by birds at outdoor restaurants and cafés, and the first to reveal interspecific differences in table-visiting behavior by birds there.

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  • 15.
    Pya Arnqvist, Natalya
    et al.
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för matematik och matematisk statistik.
    Ngendangenzwa, Blaise
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för matematik och matematisk statistik.
    Lindahl, Eric
    Volvo Group Trucks Operations.
    Nilsson, Leif
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för matematik och matematisk statistik.
    Yu, Jun
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för matematik och matematisk statistik.
    Efficient surface finish defect detection using reduced rank spline smoothers and probabilistic classifiers2021Ingår i: Econometrics and Statistics, ISSN 2452-3062, Vol. 18, s. 89-105Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    One of the primary concerns of product quality control in the automotive industry is an automated detection of defects of small sizes on specular car body surfaces. A new statistical learning approach is presented for surface finish defect detection based on spline smoothing method for feature extraction and k-nearest neighbour probabilistic classifier. Since the surfaces are specular, structured lightning reflection technique is applied for image acquisition. Reduced rank cubic regression splines are used to smooth the pixel values while the effective degrees of freedom of the obtained smooths serve as components of the feature vector. A key advantage of the approach is that it allows reaching near zero misclassification error rate when applying standard learning classifiers. In addition, probability based performance evaluation metrics have been proposed as alternatives to the conventional metrics. The usage of those provides the means for uncertainty estimation of the predictive performance of a classifier. Experimental classification results on the images obtained from the pilot system located at Volvo GTO Cab plant in Umeå, Sweden, show that the proposed approach is much more efficient than the compared methods.

  • 16.
    Pya Arnqvist, Natalya
    et al.
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för matematik och matematisk statistik.
    Arnqvist, Per
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för matematik och matematisk statistik.
    Sjöstedt de Luna, Sara
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för matematik och matematisk statistik.
    fdaMocca: Model-Based Clustering for Functional Data with Covariates. R package version 0.1-02021Övrigt (Övrigt vetenskapligt)
  • 17.
    Ghorbani, Mohammad
    et al.
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för matematik och matematisk statistik.
    Cronie, Ottmar
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för matematik och matematisk statistik. Biostatistics, School of Public Health and Community Medicine, Institute of Medicine, University of Gothenburg, Gothenburg, Sweden.
    Mateu, Jorge
    Department of Mathematics, Universitat Jaume I, Castellón, Spain.
    Yu, Jun
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för matematik och matematisk statistik.
    Functional marked point processes: a natural structure to unify spatio-temporal frameworks and to analyse dependent functional data2021Ingår i: Test (Madrid), ISSN 1133-0686, E-ISSN 1863-8260, Vol. 30, nr 3, s. 529-568Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    This paper treats functional marked point processes (FMPPs), which are defined as marked point processes where the marks are random elements in some (Polish) function space. Such marks may represent, for example, spatial paths or functions of time. To be able to consider, for example, multivariate FMPPs, we also attach an additional, Euclidean, mark to each point. We indicate how the FMPP framework quite naturally connects the point process framework with both the functional data analysis framework and the geostatistical framework. We further show that various existing stochastic models fit well into the FMPP framework. To be able to carry out nonparametric statistical analyses for FMPPs, we study characteristics such as product densities and Palm distributions, which are the building blocks for many summary statistics. We proceed to defining a new family of summary statistics, so-called weighted marked reduced moment measures, together with their nonparametric estimators, in order to study features of the functional marks. We further show how other summary statistics may be obtained as special cases of these summary statistics. We finally apply these tools to analyse population structures, such as demographic evolution and sex ratio over time, in Spanish provinces.

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  • 18.
    Pya Arnqvist, Natalya
    et al.
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för matematik och matematisk statistik.
    Voinod, Vassilly
    Makarov, Rashid
    Voinov, Yevgeniy
    nilde: Nonnegative Integer Solutions of Linear Diophantine Equations with Applications. R package version 1.1-42021Övrigt (Övrigt vetenskapligt)
  • 19.
    Sjöstedt de Luna, Sara
    et al.
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för matematik och matematisk statistik.
    Abramowicz, Konrad
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för matematik och matematisk statistik.
    Pya Arnqvist, Natalya
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för matematik och matematisk statistik.
    Non-destructive methods for assessing tree fiber length distributions in standing trees2021Manuskript (preprint) (Övrigt vetenskapligt)
    Abstract [en]

    One of the main concerns of silviculture and forest management focuses on finding fast, cost-efficient and non-destructive ways of measuring wood properties in standing trees. This paper presents an R package \verb+fiberLD+ that provides functions for estimating tree fiber length distributions in the standing tree based on increment core samples. The methods rely on increment core data measured by means of an optical fiber analyzer (OFA) or measured by microscopy. Increment core data analyzed by OFAs consist of the cell lengths of both cut and uncut fibers (tracheids) and fines (such as ray parenchyma cells) without being able to identify which cells are cut or if they are fines or fibers. The microscopy measured data consist of the observed lengths of the uncut fibers in the increment core. A censored version of a mixture of the fine and fiber length distributions is proposed to fit the OFA data, under distributional assumptions. Two choices for the assumptions of the underlying density functions of the true fiber (fine) lengths of those fibers (fines) that at least partially appear in the increment core are considered, such as the generalized gamma and the log normal densities. Maximum likelihood estimation is used for estimating the model parameters for both the OFA analyzed data and the microscopy measured data.

  • 20.
    Pya Arnqvist, Natalya
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för matematik och matematisk statistik.
    scam: Shape constrained additive models. R package version 1.2-122021Övrigt (Övrigt vetenskapligt)
  • 21.
    Pya Arnqvist, Natalya
    et al.
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för matematik och matematisk statistik.
    Lindahl, Eric
    Volvo Group Trucks Operations.
    Yu, Jun
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för matematik och matematisk statistik.
    Statistical learning of phase measuring deflectometry for defect detection and classification on specular cab body surfaces2021Ingår i: Advances in signal processing: reviews. Volume 2 / [ed] Sergey Y. Yurish, International Frequency Sensor Association Publishing , 2021, s. 309-342Kapitel i bok, del av antologi (Refereegranskat)
  • 22.
    Ghorbani, Mohammad
    et al.
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för matematik och matematisk statistik.
    Vafaei, Nafiseh
    Department of Computer and Statistics Sciences, Faculty of Sciences, Mohaghegh Ardabili University, Ardabil, Iran.
    Dvořák, Jiří
    Department of Probability and Mathematical Statistics, Faculty of Mathematics and Physics, Charles University, Prague, Czech Republic.
    Myllymäki, Mari
    Natural Resources Institute Finland (Luke), Helsinki, Finland.
    Testing the first-order separability hypothesis for spatio-temporal point patterns2021Ingår i: Computational Statistics & Data Analysis, ISSN 0167-9473, E-ISSN 1872-7352, Vol. 161, artikel-id 107245Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    First-order separability of a spatio-temporal point process plays a fundamental role in theanalysis of spatio-temporal point pattern data. While it is often a convenient assumptionthat simplifies the analysis greatly, existing non-separable structures should be accountedfor in the model construction. Three different tests are proposed to investigate thishypothesis as a step of preliminary data analysis. The first two tests are exact orasymptotically exact for Poisson processes. The first test based on permutations and globalenvelopes allows one to detect at which spatial and temporal locations or lags the datadeviate from the null hypothesis. The second test is a simple and computationally cheapχ2-test. The third test is based on stochastic reconstruction method and can be generallyapplied for non-Poisson processes. The performance of the first two tests is studied in asimulation study for Poisson and non-Poisson models. The third test is applied to the realdata of the UK 2001 epidemic foot and mouth disease.

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  • 23.
    Strandberg, Johan
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för matematik och matematisk statistik.
    Non-parametric methods for functional data2020Doktorsavhandling, sammanläggning (Övrigt vetenskapligt)
    Abstract [en]

    In this thesis we develop and study non-parametric methods within three major areas of functional data analysis: testing, clustering and prediction. The thesis consists of an introduction to the field, a presentation and discussion of the three areas, and six papers.

    In Paper I, we develop a procedure for testing for group differences in functional data. In case of significant group differences, the test procedure identifies which of the groups that significantly differ, and also the parts of the domain they do so, while controlling the type I error of falsely rejecting the null hypothesis. In Paper II, the methodology introduced in Paper I is applied to knee kinematic curves from a one-leg hop for distance to test for differences within and between three groups of individuals (with and without knee deficits). It was found that two of the groups differed in their knee kinematics. We also found that the individual kinematic patterns differed between the two legs in one of the groups. In Paper III, we test for group differences in three groups with respect to joint kinematics from a vertical one-leg hop using a novel method that allows accounting for multiple joints at the same time. The aim of Paper III, as one of few within the field of biomechanics, is to illustrate how different choices prior to the analysis can result in different contrasting conclusions. Specifically, we show how the conclusions depend on the choice of type of movement curve, the choice of leg for between-group comparisons and the included joints.

    In Paper IV, we present a new non-parametric clustering method for dependent functional data, the double clustering bagging Voronoi method. The objective of the method is to identify latent group structures that slowly vary over domain and give rise to different frequency patterns of functional data object types. The method uses a bagging strategy based on random Voronoi tessellations in which local representatives are formed and clustered. Combined with the clustering method, we also propose a multiresolution approach which allows identification of latent structures at different scales. A simulated dataset is used to illustrate the method's potential in finding stable clusters at different scales. The method is also applied to varved lake sediment data with the aim of reconstructing the climate over the past 6000 years, at different resolutions. In Paper V, we expand and modify the bagging strategy used in Paper IV, by considering different methods of generating the tessellations and clustering the local representatives of the tessellations. We propose new methods for clustering dependent categorical data (e.g., labelled functional data) along a one-dimensional domain, which we also compare in a simulation study. 

    In Paper VI, two kriging approaches to predict spatial functional processes are compared, namely functional kriging and spatio-temporal kriging. A simulation study is conducted to compare their prediction performance and computational times. The overall results show that prediction performance is about the same for stationary spatio-temporal processes while functional kriging works better for non-stationary spatio-temporal processes. Furthermore, the computational time for (ordinary) kriging for functional data, was considerably lower than spatio-temporal kriging. Conditions are also formulated under which it is proved that the two functional kriging methods: ordinary kriging for functional data and pointwise functional kriging coincide.

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  • 24.
    Pya Arnqvist, Natalya
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för matematik och matematisk statistik.
    scam: Shape constrained additive models. R package version 1.2-62020Övrigt (Övrigt vetenskapligt)
  • 25.
    Pya Arnqvist, Natalya
    et al.
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för matematik och matematisk statistik.
    Ngendangenzwa, Blaise
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för matematik och matematisk statistik.
    Lindahl, Eric
    Volvo Group Trucks Operations.
    Nilsson, Leif
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för matematik och matematisk statistik.
    A statistical learning approach for defect detection and classification on specular carbody surfaces2019Konferensbidrag (Refereegranskat)
  • 26.
    Pya Arnqvist, Natalya
    et al.
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för matematik och matematisk statistik.
    Ngendangenzwa, Blaise
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för matematik och matematisk statistik.
    Nilsson, Leif
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för matematik och matematisk statistik.
    Lindahl, Eric
    Volvo Group Trucks Operations.
    Yu, Jun
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för matematik och matematisk statistik.
    Defect detection and classfiication: statistical learning approach - Part II2019Rapport (Övrigt vetenskapligt)
  • 27.
    Pya Arnqvist, Natalya
    et al.
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för matematik och matematisk statistik.
    Ngendangenzwa, Blaise
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för matematik och matematisk statistik.
    Nilsson, Leif
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för matematik och matematisk statistik.
    Lindahl, Eric
    Volvo Group Trucks Operations.
    Yu, Jun
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för matematik och matematisk statistik.
    Effective degrees of freedom for surface finish defect detection and classification2019Manuskript (preprint) (Övrigt vetenskapligt)
    Abstract [en]

    One of the primary concerns of product quality control in the automotive industry is anautomated detection of defects of small sizes on specular car body surfaces. A new statistical learning approach is presented for surface finish defect detection based on spline smoothing method for feature extraction and k-nearest neighbour probabilistic classifier. Since the surfaces are specular, structured lightning reflection technique is applied for image acquisition. Reduced rank cubic regression splines are used to smooth the pixel values while the effective degrees of freedom of the obtained smooths serve as components of the feature vector. A key advantage of the approach is that it allows reaching near zero misclassification error ratewhen applying standard learning classifiers. We also propose probability based performance evaluation metrics as alternatives to the conventional metrics. The usage of those provides the means for uncertainty estimation of the predictive performance of a classifier. Experimental classification results on the images obtained from the pilot system located at Volvo GTO Cab plant in Umeå, Sweden, show that the proposed approach is much more efficient than the compared methods.

  • 28.
    Pya Arnqvist, Natalya
    et al.
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för matematik och matematisk statistik.
    Ngendangenzwa, Blaise
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för matematik och matematisk statistik.
    Nilsson, Leif
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för matematik och matematisk statistik.
    Lindahl, Eric
    Volvo Group Trucks Operations.
    Yu, Jun
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för matematik och matematisk statistik.
    Efficient surface finish defect detection using reduced rank spline smoothers2019Ingår i: CRoNoS & MDA 2019, 2019Konferensbidrag (Refereegranskat)
    Abstract [en]

    One of the primary concerns of product quality control in the automotive industry is an automated detection of defects of small sizes on specular car body surfaces. A new statistical learning approach is presented for surface finish defect detection based on spline smoothing method for feature extraction and k-nearest neighbor probabilistic classifier. Rather than analyzing the natural images of the car body surfaces, the deflectometry technique is applied for image acquisition. Reduced rank cubic regression splines are used to smooth the pixel values while the effective degrees of freedom of the obtained smooths serve as components of the feature vector. A key advantage of the approach is that it allows us to reach near zero misclassification error when applying standard learning classifiers. We also propose the probability based performance evaluation metrics as alternatives to the conventional metrics. The usage of those provides the means for uncertainty estimation of the predictive performance of a classifier. Experimental classification results on the images obtained from the pilot system located at Volvo cab plant in Umea, Sweden, show that the proposed approach is much more efficient than compared methods.

  • 29.
    Pya Arnqvist, Natalya
    et al.
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för matematik och matematisk statistik.
    Sjöstedt de Luna, Sara
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för matematik och matematisk statistik.
    Abramowicz, Konrad
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för matematik och matematisk statistik.
    fiberLD: Fiber Length Determination. R package version 0.1-62019Övrigt (Övrigt vetenskapligt)
  • 30.
    Ghorbani, Mohammad
    et al.
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för matematik och matematisk statistik.
    Cronie, Ottmar
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för matematik och matematisk statistik.
    Mateu, Jorge
    Department of Mathematics, Universitat Jaume I, Castellón, Spain.
    Yu, Jun
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för matematik och matematisk statistik.
    Functional marked point processes: a natural structure to unify spatio-temporal frameworks and to analyse dependent functional data2019Ingår i: 20th Workshop on Stochastic Geometry, Stereology and Image Analysis 2–7 June, 2019, Sandbjerg Estate, Denmark: Abstract book, 2019, s. 13-13Konferensbidrag (Övrigt vetenskapligt)
  • 31.
    Cronie, Ottmar
    et al.
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för matematik och matematisk statistik.
    Ghorbani, Mohammad
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för matematik och matematisk statistik.
    Yu, Jun
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för matematik och matematisk statistik.
    Mateu, Jorge
    Department of Mathematics, Universitat Jaume I, Castellón, Spain.
    Functional marked point processes: Unifying spatio-temporal frameworks and analysing spatially dependent functional data2019Ingår i: Statistical Analysis for Space-Time Data: Pragramme and Abstract Book, Eurpean Courses in Advanced Statistics (ECAS) , 2019, s. 7-7Konferensbidrag (Refereegranskat)
    Abstract [en]

    This paper treats functional marked point processes (FMPPs), which are defined as marked point processes where the marks are random elements in some (Polish) function space. Such marks may represent e.g. spatial paths or functions of time. To be able to consider e.g. multivariate FMPPs, we also attach an additionally, Euclidean, mark to each point. We indicate how the FMPP framework quite naturally connects the point process framework with both the functional data analysis framework and the geostatistical framework; in particular we define spatio-temporal geostatistical marking for point processes. We further show that various existing stochastic models fit well into the FMPP framework, in particular marked point processes with real valued marks. To be able to carry out non-parametric statistical analyses for functional marked point patterns, we study characteristics such as product densities and Palm distributions, which are the building blocks for summary statistics such as marked inhomogeneous J-functions and our so-called K-functionals. We finally apply these statistical tools to analyse a few different functional marked point patterns.

  • 32.
    Abramowicz, Konrad
    et al.
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för matematik och matematisk statistik.
    Schelin, Lina
    Umeå universitet, Samhällsvetenskapliga fakulteten, Handelshögskolan vid Umeå universitet, Statistik.
    Sjöstedt de Luna, Sara
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för matematik och matematisk statistik.
    Strandberg, Johan
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för matematik och matematisk statistik.
    Multiresolution clustering of dependent functional data with application to climate reconstruction2019Ingår i: Stat, E-ISSN 2049-1573, Vol. 8, nr 1, artikel-id e240Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    We propose a new nonparametric clustering method for dependent functional data, the double clustering bagging Voronoi method. It consists of two levels of clustering. Given a spatial lattice of points, a function is observed at each grid point. In the first‐level clustering, features of the functional data are clustered. The second‐level clustering takes dependence into account, by grouping local representatives, built from the resulting first‐level clusters, using a bagging Voronoi strategy. Depending on the distance measure used, features of the functions may be included in the second‐step clustering, making the method flexible and general. Combined with the clustering method, a multiresolution approach is proposed that searches for stable clusters at different spatial scales, aiming to capture latent structures. This provides a powerful and computationally efficient tool to cluster dependent functional data at different spatial scales, here illustrated by a simulation study. The introduced methodology is applied to varved lake sediment data, aiming to reconstruct winter climate regimes in northern Sweden at different time resolutions over the past 6,000 years.

  • 33.
    Pya Arnqvist, Natalya
    et al.
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för matematik och matematisk statistik.
    Voinov, Vassilly
    Voinov, Yevgeniy
    nilde: Nonnegative Integer Solutions of Linear Diophantine Equations with Applications. R package version 1.1-32019Övrigt (Övrigt vetenskapligt)
  • 34.
    Strandberg, Johan
    et al.
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för matematik och matematisk statistik.
    Sjöstedt de Luna, Sara
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för matematik och matematisk statistik.
    Mateu, Jorge
    Prediction of spatial functional random processes: comparing functional and spatio-temporal kriging approaches2019Ingår i: Stochastic environmental research and risk assessment (Print), ISSN 1436-3240, E-ISSN 1436-3259, Vol. 33, nr 10, s. 1699-1719Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    We present and compare functional and spatio-temporal (Sp.T.) kriging approaches to predict spatial functional random processes (which can also be viewed as Sp.T. random processes). Comparisons with respect to computational time and prediction performance via functional cross-validation is evaluated, mainly through a simulation study but also on a real data set. We restrict comparisons to Sp.T. kriging versus ordinary kriging for functional data (OKFD), since the more flexible functional kriging approaches pointwise functional kriging (PWFK) and the functional kriging total model coincide with OKFD in several situations. Here we formulate conditions under which we show that OKFD and PWFK coincide. From the simulation study, it is concluded that the prediction performance of the two kriging approaches in general is rather equal for stationary Sp.T. processes. However, functional kriging tends to perform better for small sample sizes, while Sp.T. kriging works better for large sizes. For non-stationary Sp.T. processes, with a common deterministic time trend and/or time varying variances and dependence structure, OKFD performs better than Sp.T. kriging irrespective of the sample size. For all simulated cases, the computational time for OKFD was considerably lower compared to those for the Sp.T. kriging methods.

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  • 35.
    Pya Arnqvist, Natalya
    et al.
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för matematik och matematisk statistik.
    Ngendangenzwa, Blaise
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för matematik och matematisk statistik.
    Nilsson, Leif
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för matematik och matematisk statistik.
    Lindahl, Eric
    Volvo Group Trucks Operations.
    Yu, Jun
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för matematik och matematisk statistik.
    Automated surface finish defect detection using statistical learning approach2018Konferensbidrag (Övrigt vetenskapligt)
  • 36.
    Pya Arnqvist, Natalya
    et al.
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för matematik och matematisk statistik.
    Ngendangenzwa, Blaise
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för matematik och matematisk statistik.
    Nilsson, Leif
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för matematik och matematisk statistik.
    Lindahl, Eric
    Volvo Group Trucks Operations.
    Yu, Jun
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för matematik och matematisk statistik.
    Defect detection and classification: statistical learning approach2018Rapport (Övrigt vetenskapligt)
  • 37.
    Rani, Raffaele
    et al.
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för matematik och matematisk statistik.
    Abramowicz, Konrad
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för matematik och matematisk statistik.
    Falster, Daniel S.
    Sterck, Frank
    Brännström, Åke
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för matematik och matematisk statistik. Evolution and Ecology Program, International Institute for Applied Systems Analysis, Laxenburg, Austria.
    Effects of bud-flushing strategies on tree growth2018Ingår i: Tree Physiology, ISSN 0829-318X, E-ISSN 1758-4469, Vol. 38, nr 9, s. 1384-1393Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Allocation of carbohydrates between competing organs is fundamental to plant development, growth and productivity. Carbohydrates are synthesized in mature leaves and distributed via the phloem vasculature to developing buds where they are consumed to produce new biomass. The distribution and mass-allocation processes within the plant remain poorly understood and may involve complex feedbacks between different plant functions, with implications for the emergent structure of the plant. Here, we investigate how the order in which dormant buds are flushed affects the development of tree size and reproductive output during the first 20 years of growth in full light and shaded canopy environments. We report the following findings: (i) Bud-flushing strategies strongly affect the temporal dynamics of height, mass and the size of reproduction pool, as well as the resulting architectures. (ii) Bud-flushing strategies affect tree growth by altering the rate of growth and final size of trees. (iii) No single bud-flushing strategy performs best when both the size and allocation for reproduction of the resulting trees are compared. However, we observe that the strategy that optimizes the net carbon gain for the entire tree architecture always results in a high reproduction output. (iv) Branch turnover and meristem regeneration enhance the performance of certain strategies with respect to the measured quantities. These results highlight the importance of employing generic models of architecture (i.e., non-species-specific) to identify general mechanisms of carbon allocation and the spatial distribution of newly formed biomass in growing trees.

  • 38. Wenk, Elizabeth Hedi
    et al.
    Abramowicz, Konrad
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för matematik och matematisk statistik.
    Westoby, Mark
    Falster, Daniel S.
    Investment in reproduction for 14 iteroparous perennials is large and associated with other life-history and functional traits2018Ingår i: Journal of Ecology, ISSN 0022-0477, E-ISSN 1365-2745, Vol. 106, nr 4, s. 1338-1348Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    1. While theoretical models predict reproductive allocation (RA) should approach 100% of available energy as a plant ages, available empirical data suggest much lower RA values in perennial plants. In this study, we have two aims. First, we assess whether the discrepancy between theory and data arises from methodological differences in how growth and RA are calculated. Specifically, we hypothesize RA in older plants is large when compared to growth in leaf area, that is, after excluding turnover of stem and leaf tissues. Second, we hypothesize that species with cheap tissues or those that are shorter reach RA = 0.5 at a younger age.

    2. We measured investment in leaf, stem and reproduction on individuals from 14 co-occurring woody perennial iteroparous species. A fire chronosequence allowed us to use a space-for-time substitution to estimate RA schedules for each species, simultaneously measuring reproductive and vegetative production on individuals differing in age.

    3. For most (11 of 14) species, we found RA eventually reached 100% of available energy, with another two species reaching at least 80%. Increases in RA were associated with a decline in growth of leaf area. Comparing species, we found that species with cheap leaves reached RA = 0.5 sooner (they could be called fast-living), whereas delayed maturation and slower increases in RA were associated with greater maximum height.

    4. Synthesis. Explicitly accounting for the cost of leaf replacement leads to the high estimates of reproductive allocation in perennial plants predicted by theoretical models, limiting or even halting leaf area expansion. For some species, so much energy is allocated to reproduction that leaf area declines year-upon-year for multiple growing seasons preceding death. Connecting lifetime reproductive allocation schedules with leaf area expansion, leaf life span, and plant maximum height demonstrates how reproductive allocation schedules synthesize a plant's life-history strategy, making them a valuable tool for connecting plant traits and demography.

  • 39.
    Abramowicz, Konrad
    et al.
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för matematik och matematisk statistik.
    Häger, Charlotte
    Umeå universitet, Medicinska fakulteten, Institutionen för samhällsmedicin och rehabilitering, Fysioterapi.
    Pini, Alessia
    Umeå universitet, Samhällsvetenskapliga fakulteten, Handelshögskolan vid Umeå universitet, Statistik. Department of Statistical Sciences, Università Cattolica del Sacro Cuore, Milan, Italy.
    Schelin, Lina
    Umeå universitet, Medicinska fakulteten, Institutionen för samhällsmedicin och rehabilitering. Umeå universitet, Samhällsvetenskapliga fakulteten, Handelshögskolan vid Umeå universitet, Statistik.
    Sjöstedt de Luna, Sara
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för matematik och matematisk statistik.
    Vantini, Simone
    Nonparametric inference for functional-on-scalar linear models applied to knee kinematic hop data after injury of the anterior cruciate ligament2018Ingår i: Scandinavian Journal of Statistics, ISSN 0303-6898, E-ISSN 1467-9469, Vol. 45, nr 4, s. 1036-1061Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Motivated by the analysis of the dependence of knee movement patterns during functional tasks on subject-specific covariates, we introduce a distribution-free procedure for testing a functional-on-scalar linear model with fixed effects. The procedure does not only test the global hypothesis on the entire domain but also selects the intervals where statistically significant effects are detected. We prove that the proposed tests are provided with an asymptotic control of the intervalwise error rate, that is, the probability of falsely rejecting any interval of true null hypotheses. The procedure is applied to one-leg hop data from a study on anterior cruciate ligament injury. We compare knee kinematics of three groups of individuals (two injured groups with different treatments and one group of healthy controls), taking individual-specific covariates into account.

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  • 40. Voinov, Vassilly
    et al.
    Pya Arnqvist, Natalya
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för matematik och matematisk statistik.
    Voinov, Yevgeniy
    Polynomial in time nonnegative integer solutions of knapsacks and similar problems in R: P=NP?2018Ingår i: Mathematical Journal, ISSN 1682-0525, Vol. 18, nr 2, s. 47-58Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    A new result is the well forgotten old one"(A Russian proverb) Annotation. An R-package "nilde" [1] for the enumeration of all existing nonnegative integer solutions of linear Diophantine equations and inequalities and related problems is presented. The software uses the approach based on a generating function of Hardy and Littlewood [2] introduced in 1966 and the algorithm proposed by Voinov and Nikulin [3] in 1997. The package proves to be useful for solving 0-1, bounded and unbounded knapsacks, subset sum problems, integer linear programs, partitioning of natural numbers, etc. The main advantage of the proposed software is that it solves all the above problems in polynomial time. Numerous examples illustrate applications of the package. Strong theoretical and empirical arguments in favor of equality P=NP are presented.

  • 41.
    Abramowizc, Konrad
    et al.
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för matematik och matematisk statistik.