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  • 1.
    Abramowicz, Konrad
    et al.
    Umeå University, Faculty of Science and Technology, Department of Mathematics and Mathematical Statistics.
    Häger, Charlotte
    Umeå University, Faculty of Medicine, Department of Community Medicine and Rehabilitation, Physiotherapy.
    Pini, Alessia
    Umeå University, Faculty of Social Sciences, Umeå School of Business and Economics (USBE), Statistics. Department of Statistical Sciences, Università Cattolica del Sacro Cuore, Milan, Italy.
    Schelin, Lina
    Umeå University, Faculty of Medicine, Department of Community Medicine and Rehabilitation. Umeå University, Faculty of Social Sciences, Umeå School of Business and Economics (USBE), Statistics.
    Sjöstedt de Luna, Sara
    Umeå University, Faculty of Science and Technology, Department of Mathematics and Mathematical Statistics.
    Vantini, Simone
    Nonparametric inference for functional-on-scalar linear models applied to knee kinematic hop data after injury of the anterior cruciate ligament2018In: Scandinavian Journal of Statistics, ISSN 0303-6898, E-ISSN 1467-9469, Vol. 45, no 4, p. 1036-1061Article in journal (Refereed)
    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.

  • 2.
    Belyaev, Yuri K
    et al.
    Umeå University, Faculty of Science and Technology, Department of Mathematics and Mathematical Statistics.
    Seleznjev, Oleg
    Moscow state university.
    Approaching in distribution with applications to resampling of stochastic processes2000In: Scandinavian Journal of Statistics, ISSN 0303-6898, E-ISSN 1467-9469, Vol. 27, no 2, p. 371-384Article in journal (Refereed)
    Abstract [en]

    We introduce the notion of weak approaching and conditionally weak approaching sequences of random processes. This notion generalizes the conventional weak convergence, and has been proposed for real valued random variables in Belyaev (1995). Some of the standard tools for an investigation of the behaviour of weak approaching sequences of random elements in metric spaces are developed. The spaces of smoothed and right-continuous functions with left-hand limits are considered. This technique allows us to use the resampling approach for an evaluation of distributions of continuous functionals on realizations of sum of an increasing number of independent random processes. Two numerical examples are presented for such functionals as supremum and number of level crossings.

  • 3.
    Bolin, David
    Umeå University, Faculty of Science and Technology, Department of Mathematics and Mathematical Statistics.
    Spatial Matern Fields Driven by Non-Gaussian Noise2014In: Scandinavian Journal of Statistics, ISSN 0303-6898, E-ISSN 1467-9469, Vol. 41, no 3, p. 557-579Article in journal (Refereed)
    Abstract [en]

    The article studies non-Gaussian extensions of a recently discovered link between certain Gaussian random fields, expressed as solutions to stochastic partial differential equations (SPDEs), and Gaussian Markov random fields. The focus is on non-Gaussian random fields with Matern covariance functions, and in particular, we show how the SPDE formulation of a Laplace moving-average model can be used to obtain an efficient simulation method as well as an accurate parameter estimation technique for the model. This should be seen as a demonstration of how these techniques can be used, and generalizations to more general SPDEs are readily available.

  • 4.
    Bondesson, Lennart
    Umeå University, Faculty of Science and Technology, Department of Mathematics and Mathematical Statistics.
    Conditional and restricted Pareto sampling: two new methods for unequal probability sampling2010In: Scandinavian Journal of Statistics, ISSN 0303-6898, E-ISSN 1467-9469, Vol. 37, no 3, p. 514-530Article in journal (Refereed)
    Abstract [en]

    Two new unequal probability sampling methods are introduced: conditional and restricted Pareto sampling. The advantage of conditional Pareto sampling compared with standard Pareto sampling, introduced by Rosén (J. Statist. Plann. Inference, 62, 1997, 135, 159), is that the factual inclusion probabilities better agree with the desired ones. Restricted Pareto sampling, preferably conditioned or adjusted, is able to handle cases where there are several restrictions on the sample and is an alternative to the recent cube method for balanced sampling introduced by Deville and Tillé (Biometrika, 91, 2004, 893). The new sampling designs have high entropy and the involved random numbers can be seen as permanent random numbers.

  • 5.
    Bondesson, Lennart
    Umeå University, Faculty of Science and Technology, Department of Mathematics and Mathematical Statistics.
    Dear reader,2001In: Scandinavian Journal of Statistics, ISSN 0303-6898, E-ISSN 1467-9469, Vol. 28, no 1, p. 1-1Article in journal (Other academic)
  • 6.
    Bondesson, Lennart
    Umeå University, Faculty of Science and Technology, Department of Mathematics and Mathematical Statistics.
    On Sampling with Prescribed Second-order Inclusion Probabilities2012In: Scandinavian Journal of Statistics, ISSN 0303-6898, E-ISSN 1467-9469, Vol. 39, no 4, p. 813-829Article in journal (Refereed)
    Abstract [en]

    Methods to perform fixed size sampling with prescribed second-order inclusion probabilities are presented. The focus is on a conditional Poisson design of order 2, a CP(2) design. It is an exponential design of quadratic type and it is carefully studied. In particular, methods to find the suitable values of the parameters and methods to sample are described. Small examples illustrate.

  • 7.
    Bondesson, Lennart
    et al.
    Umeå University, Faculty of Science and Technology, Department of Mathematics and Mathematical Statistics.
    Fahlén, Jessica
    Umeå University, Faculty of Science and Technology, Department of Mathematics and Mathematical Statistics.
    Mean and variance of vacancy for hard-core Disc processes and applications2003In: Scandinavian Journal of Statistics, ISSN 0303-6898, E-ISSN 1467-9469, Vol. 30, no 4, p. 797-816Article in journal (Refereed)
  • 8.
    Bondesson, Lennart
    et al.
    Umeå University, Faculty of Science and Technology, Department of Mathematics and Mathematical Statistics.
    Grafström, Anton
    Umeå University, Faculty of Science and Technology, Department of Mathematics and Mathematical Statistics.
    An extension of Sampford's method for unequal probability sampling2011In: Scandinavian Journal of Statistics, ISSN 0303-6898, E-ISSN 1467-9469, Vol. 38, no 2, p. 377-392Article in journal (Other academic)
    Abstract [en]

    Sampford's (1967) unequal probability sampling method is extended to the case that the inclusion probabilities do not sum to an integer. In this case the sampling outcome is left open for exactly one randomly chosen unit and that unit gets a new inclusion probability. Three applications are presented. Two of them challenge traditional sampling routines. The simple Pareto sampling design, which was introduced by Rosén (1997a,b), is also extended. The extended Pareto design is shown to be close to the extended Sampford design.

  • 9.
    Bondesson, Lennart
    et al.
    Umeå University, Faculty of Science and Technology, Department of Mathematics and Mathematical Statistics.
    Thorburn, Daniel
    Department of Statistics, University of Stockholm.
    A list sequential sampling method suitable for real time sampling2008In: Scandinavian Journal of Statistics, ISSN 0303-6898, E-ISSN 1467-9469, Vol. 35, no 3, p. 466-483Article in journal (Refereed)
    Abstract [en]

    A flexible list sequential πps sampling method is introduced and studied. It can reproduce any given sampling design without replacement, of fixed or random sample size. The method is a splitting method and uses successive updating of inclusion probabilities. The main advantage of the method is in real-time sampling situations where it can be used as a powerful alternative to Bernoulli and Poisson sampling and can give any desired second-order inclusion probabilities and thus considerably reduce the variability of the sample size.

  • 10.
    Bondesson, Lennart
    et al.
    Umeå University, Faculty of Science and Technology, Department of Mathematics and Mathematical Statistics.
    Traat, Imbi
    On Sampling Designs with Ordered Conditional Inclusion Probabilities2013In: Scandinavian Journal of Statistics, ISSN 0303-6898, E-ISSN 1467-9469, Vol. 40, no 4, p. 724-733Article in journal (Refereed)
    Abstract [en]

    In this paper we consider a family of sampling designs for which increasing first-order inclusion probabilities imply, in a specific sense, increasing conditional inclusion probabilities. It is proved that the complementary Midzuno, the conditional Poisson, and the Sampford designs belong to this family. It is shown that designs of the family are more efficient than a comparable with-replacement design. Furthermore, the efficiency gain is explicitly given for these designs.

  • 11.
    Bondesson, Lennart
    et al.
    Umeå University, Faculty of Science and Technology, Department of Mathematics and Mathematical Statistics.
    Traat, Imbi
    Institute of Mathematical Statistics , University of Tartu , Estonia.
    Lundquist, Anders
    Umeå University, Faculty of Science and Technology, Department of Mathematics and Mathematical Statistics.
    Pareto sampling versus Sampford and Conditional Poisson sampling2006In: Scandinavian Journal of Statistics, ISSN 0303-6898, E-ISSN 1467-9469, Vol. 33, no 4, p. 699-720Article in journal (Refereed)
    Abstract [en]

    Pareto sampling was introduced by Rosén in the late 1990s. It is a simple method to get a fixed size πps sample though with inclusion probabilities only approximately as desired. Sampford sampling, introduced by Sampford in 1967, gives the desired inclusion probabilities but it may take time to generate a sample. Using probability functions and Laplace approximations, we show that from a probabilistic point of view these two designs are very close to each other and asymptotically identical. A Sampford sample can rapidly be generated in all situations by letting a Pareto sample pass an acceptance–rejection filter. A new very efficient method to generate conditional Poisson (CP) samples appears as a byproduct. Further, it is shown how the inclusion probabilities of all orders for the Pareto design can be calculated from those of the CP design. A new explicit very accurate approximation of the second-order inclusion probabilities, valid for several designs, is presented and applied to get single sum type variance estimates of the Horvitz–Thompson estimator.

  • 12.
    Broström, Göran
    Umeå University, Faculty of Social Sciences, Department of Statistics.
    The influence of mother's mortality on infant mortality, A case study in matched data survival analysis1987In: Scandinavian Journal of Statistics, ISSN 0303-6898, E-ISSN 1467-9469, Vol. 14, p. 113-123Article in journal (Refereed)
  • 13.
    Cronie, Ottmar
    et al.
    CWI, Amsterdam, The Netherlands.
    van Lieshout, M N M
    CWI, Amsterdam, The Netherlands.
    J-function for Inhomogeneous Spatio-temporal Point Processes2015In: Scandinavian Journal of Statistics, ISSN 0303-6898, E-ISSN 1467-9469, Vol. 42, no 2, p. 562-579Article in journal (Refereed)
    Abstract [en]

    We propose a new summary statistic for inhomogeneous intensity-reweighted moment stationarity spatio-temporal point processes. The statistic is defined in terms of the n-point correlation functions of the point process, and it generalizes the J-function when stationarity is assumed. We show that our statistic can be represented in terms of the generating functional and that it is related to the spatio-temporal K-function. We further discuss its explicit form under some specific model assumptions and derive ratio-unbiased estimators. We finally illustrate the use of our statistic in practice.

  • 14.
    Ekström, Magnus
    Department of Forest Resource Management and Geomatics, Swedish University of Agricultural Sciences, Umeå.
    Consistency of generalized maximum spacing estimates2001In: Scandinavian Journal of Statistics, ISSN 0303-6898, E-ISSN 1467-9469, Vol. 28, no 2, p. 343-354Article in journal (Refereed)
    Abstract [en]

    General methods for the estimation of distributions can be derived from approximations of certain information measures. For example, both the maximum likelihood (ML) method and the maximum spacing (MSP) method can be obtained from approximations of the Kullback–Leibler information. The ideas behind the MSP method, whereby an estimation method for continuous univariate distributions is obtained from an approximation based on spacings of an information measure, were used by Ranneby & Ekstrom (1997) (using simple spacings) and Ekstrom (1997b) (using high order spacings) to obtain a class of methods, called generalized maximum spacing (GMSP) methods. In the present paper, GMSP methods will be shown to give consistent estimates under general conditions, comparable to those of Bahadur (1971) for the ML method, and those of Shao & Hahn (1999) for the MSP method. In particular, it will be proved that GMSP methods give consistent estimates in any family of distributions with unimodal densities, without any further conditions on the distributions.

  • 15.
    Ekström, Magnus
    Umeå University, Faculty of Social Sciences, Umeå School of Business and Economics (USBE), Statistics.
    Powerful parametric tests based on sum-functions of spacings2013In: Scandinavian Journal of Statistics, ISSN 0303-6898, E-ISSN 1467-9469, Vol. 40, no 4, p. 886-898Article in journal (Refereed)
    Abstract [en]

    Assume that we have a sequence of n independent and identically distributed random variables with a continuous distribution function F, which is specified up to a few unknown parameters. In this paper, tests based on sum-functions of sample spacings are proposed, and large sample theory of the tests are presented under simple null hypotheses as well as under close alternatives. Tests, which are optimal within this class, are constructed, and it is noted that these tests have properties that closely parallel those of the likelihood ratio test in regular parametric models. Some examples are given, which show that the proposed tests work also in situations where the likelihood ratio test breaks down. Extensions to more general hypotheses are discussed.

  • 16.
    Ekström, Magnus
    Centre of Biostochastics, Swedish University of Agricultural Sciences, Umeå.
    Subsampling variance estimation for nonstationary spatial lattice data2008In: Scandinavian Journal of Statistics, ISSN 0303-6898, E-ISSN 1467-9469, Vol. 35, no 1, p. 38-63Article in journal (Refereed)
    Abstract [en]

    Most proposed subsampling and resampling methods in the literature assume stationary data. In many empirical applications, however, the hypothesis of stationarity can easily be rejected. In this paper, we demonstrate that moment and variance estimators based on the subsampling methodology can also be employed for different types of non-stationarity data. Consistency of estimators are demonstrated under mild moment and mixing conditions. Rates of convergence are provided, giving guidance for the appropriate choice of subshape size. Results from a small simulation study on finite-sample properties are also reported.

  • 17.
    Grafström, Anton
    et al.
    Department of Forest Resource Management, Swedish University of Agricultural Sciences, Umeå, Sweden.
    Schelin, Lina
    Umeå University, Faculty of Science and Technology, Department of Mathematics and Mathematical Statistics.
    How to Select Representative Samples2014In: Scandinavian Journal of Statistics, ISSN 0303-6898, E-ISSN 1467-9469, Vol. 41, no 2, p. 277-290Article in journal (Refereed)
    Abstract [en]

    We give a formal definition of a representative sample, but roughly speaking, it is a scaled-down version of the population, capturing its characteristics. New methods for selecting representative probability samples in the presence of auxiliary variables are introduced. Representative samples are needed for multipurpose surveys, when several target variables are of interest. Such samples also enable estimation of parameters in subspaces and improved estimation of target variable distributions. We describe how two recently proposed sampling designs can be used to produce representative samples. Both designs use distance between population units when producing a sample. We propose a distance function that can calculate distances between units in general auxiliary spaces. We also propose a variance estimator for the commonly used Horvitz–Thompson estimator. Real data as well as illustrative examples show that representative samples are obtained and that the variance of the Horvitz–Thompson estimator is reduced compared with simple random sampling.

  • 18.
    Iftimi, Adina
    et al.
    Department of Biosciences and Nutrition, Karolinska Institutet, Stockholm, Sweden.
    Cronie, Ottmar
    Umeå University, Faculty of Science and Technology, Department of Mathematics and Mathematical Statistics.
    Montes, Francisco
    Department of Statistics and Operations Research, University of Valencia, Valencia, Spain.
    Second-order analysis of marked inhomogeneous spatio-temporal point processes: applications to earthquake data2019In: Scandinavian Journal of Statistics, ISSN 0303-6898, E-ISSN 1467-9469, Vol. 46, no 3, p. 661-685Article in journal (Refereed)
    Abstract [en]

    To analyse interactions in marked spatio-temporal point processes (MSTPPs), we introduce marked second-order reduced moment measures and K-functions for inhomogeneous second-order intensity reweighted stationary MSTPPs. These summary statistics, which allow us to quantify dependence between different mark-based classifications of the points, are depending on the specific mark space and mark reference measure chosen. Unbiased and consistent minus-sampling estimators are derived for all statistics considered and a test for random labelling is indicated. In addition, we treat Voronoi intensity estimators for MSTPPs. These new statistics are finally employed to analyse an Andaman sea earthquake data set.

  • 19.
    Kuljus, Kristi
    et al.
    Umeå University, Faculty of Science and Technology, Department of Mathematics and Mathematical Statistics.
    Ranneby, Bo
    Generalized Maximum Spacing Estimation for Multivariate Observations2015In: Scandinavian Journal of Statistics, ISSN 0303-6898, E-ISSN 1467-9469, Vol. 42, no 4, p. 1092-1108Article in journal (Refereed)
    Abstract [en]

    In this paper, the maximum spacing method is considered for multivariate observations. Nearest neighbour balls are used as a multidimensional analogue to univariate spacings. A class of information-type measures is used to generalize the concept of maximum spacing estimators. Weak and strong consistency of these generalized maximum spacing estimators are proved both when the assigned model class is correct and when the true density is not a member of the model class. An example of the generalized maximum spacing method in model validation context is discussed.

  • 20.
    Persson, Anna H.
    et al.
    Global Biometric Sciences, Bristol-Myers Squibb Company.
    Bondesson, Lennart
    Umeå University, Faculty of Science and Technology, Department of Mathematics and Mathematical Statistics.
    Börlin, Niclas
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Estimation of polygons and areas2006In: Scandinavian Journal of Statistics, ISSN 0303-6898, E-ISSN 1467-9469, Vol. 33, no 3, p. 541-559Article in journal (Refereed)
    Abstract [en]

    In forestry the problem of estimating areas is central. This paper addresses area estimation through fitting of a polygon to observed coordinate data. Coordinates of corners and points along the sides of a simple closed polygon are measured with independent random errors. This paper focuses on procedures to adjust the coordinates for estimation of the polygon and its area. Different new techniques that consider different amounts of prior information are described and compared. The different techniques use restricted least squares, maximum likelihood and the expectation maximization algorithm. In a simulation study it is shown that the root mean square errors of the estimates are decreased when coordinates are adjusted before estimation. Minor further improvement is achieved by using prior information about the order and the distribution of the points along the sides of the polygon. This paper has its origin in forestry but there are also other applications.

  • 21.
    Sjöstedt de Luna, Sara
    et al.
    Umeå University, Faculty of Science and Technology, Department of Mathematics and Mathematical Statistics.
    Young, Alastair
    The bootstrap and kriging prediction intervals2003In: Scandinavian Journal of Statistics, ISSN 0303-6898, E-ISSN 1467-9469, Vol. 30, p. 175-192Article in journal (Refereed)
  • 22.
    Sjöstedt de Luna, Sara
    et al.
    Umeå University, Faculty of Science and Technology, Department of Mathematics and Mathematical Statistics.
    Young, Alastair
    The bootstrap and kriging prediction intervals2003In: Scandinavian Journal of Statistics, ISSN 0303-6898, E-ISSN 1467-9469, Vol. 30, p. 175-192Article in journal (Refereed)
  • 23.
    Sjöstedt, Sara
    Umeå University, Faculty of Science and Technology, Department of Mathematics and Mathematical Statistics.
    Resampling m-dependent random variables with applications to forecasting.2000In: Scandinavian Journal of Statistics, ISSN 0303-6898, E-ISSN 1467-9469, Vol. 27, p. 543-562Article in journal (Refereed)
  • 24.
    Sjöstedt, Sara
    Umeå University, Faculty of Science and Technology, Department of Mathematics and Mathematical Statistics.
    Resampling m-dependent random variables with applications to forecasting2000In: Scandinavian Journal of Statistics, ISSN 0303-6898, E-ISSN 1467-9469, Vol. 27, p. 543-562Article in journal (Refereed)
  • 25.
    Svensson, Ingrid
    et al.
    Umeå University, Faculty of Science and Technology, Department of Mathematics and Mathematical Statistics.
    Sjöstedt-de Luna, Sara
    Umeå University, Faculty of Science and Technology, Department of Mathematics and Mathematical Statistics.
    Bondesson, Lennart
    Umeå University, Faculty of Science and Technology, Department of Mathematics and Mathematical Statistics.
    Estimation of wood fibre length distributions from censored data through an EM algorithm2006In: Scandinavian Journal of Statistics, ISSN 0303-6898, E-ISSN 1467-9469, Vol. 33, no 3, p. 503-522Article in journal (Refereed)
1 - 25 of 25
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