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  • 1.
    Broström, Göran
    Umeå universitet, Samhällsvetenskaplig fakultet, Statistik.
    A modification of Fisher's omnibus test1998Inngår i: Communications in Statistics - Theory and Methods, ISSN 0361-0926, E-ISSN 1532-415X, Vol. 27, s. 2663-2674Artikkel i tidsskrift (Fagfellevurdert)
  • 2.
    Broström, Göran
    Umeå universitet, Samhällsvetenskaplig fakultet, Statistik.
    On sequentially rejective subset selection procedures1981Inngår i: Communications in Statistics - Theory and Methods, ISSN 0361-0926, E-ISSN 1532-415X, Vol. A10, nr 3, s. 203-221Artikkel i tidsskrift (Fagfellevurdert)
  • 3.
    Brännäs, Kurt
    et al.
    Umeå universitet, Samhällsvetenskapliga fakulteten, Institutionen för nationalekonomi.
    Brännäs, Eva
    Conditional Heteroskedasticity in Count Data Regression: Self-Feeding Activity in Fish2004Inngår i: Communications in Statistics - Theory and Methods, ISSN 0361-0926, E-ISSN 1532-415X, Vol. 33, nr 11, s. 2745-2758Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    This paper introduces a new approach to incorporating time-dependent overdispersion for Poisson-related regression models. To handle the added flexibility in conditional heteroskedasticity in time series count data models, some well-known estimators are adapted, and a generalized method of moments (GMM) estimator is suggested. The estimators are applied to a time series of self-feeding activity in Arctic charr. There is strong support for both a dynamic conditional mean function and a dynamic model for the overdispersion.

  • 4.
    Brännäs, Kurt
    et al.
    Umeå universitet, Samhällsvetenskapliga fakulteten, Handelshögskolan vid Umeå universitet, Nationalekonomi.
    De Gooijer, J. G.
    Teräsvirta, T.
    Testing linearity against nonlinear moving average models1998Inngår i: Communications in Statistics - Theory and Methods, ISSN 0361-0926, E-ISSN 1532-415X, Vol. 27, nr 8, s. 2025-2035Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Lagrange multiplier (LM) test statistics are derived for testing a linear moving average model against an asymmetric moving average model and an LM type test against an additive smooth transition moving average model. The latter model is introduced in the paper. The small sample performance of the proposed tests are evaluated in a Monte Carlo study and compared to Wald and likelihood ratio statistics. The size properties of the Lagrange multiplier test are better than those of other tests.

  • 5.
    Brännäs, Kurt
    et al.
    Umeå universitet, Samhällsvetenskapliga fakulteten, Handelshögskolan vid Umeå universitet, Nationalekonomi.
    Johansson, Per
    Umeå universitet, Samhällsvetenskapliga fakulteten, Handelshögskolan vid Umeå universitet, Nationalekonomi.
    Time-series count data regression1994Inngår i: Communications in Statistics - Theory and Methods, ISSN 0361-0926, E-ISSN 1532-415X, Vol. 23, nr 10, s. 2907-2925Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    The count data model studied in the paper extends the Poisson model by allowing for overdispersion and serial correlation. Alternative approaches to estimate nuisance parameters, required for the correction of the Poisson maximum likelihood covariance matrix estimator and for a quasi-likelihood estimator, are studied. The estimators are evaluated by finite sample Monte Carlo experimentation. It is found that the Poisson maximum likelihood estimator with corrected covariance matrix estimators provide reliable inferences for longer time series. Overdispersion test statistics are wellbehaved, while conventional portmanteau statistics for white noise have too large sizes. Two empirical illustrations are included.

  • 6.
    Brännäs, Kurt
    et al.
    Umeå universitet, Samhällsvetenskapliga fakulteten, Handelshögskolan vid Umeå universitet, Statistik.
    Uhlin, Stig
    Umeå universitet, Samhällsvetenskapliga fakulteten, Handelshögskolan vid Umeå universitet, Statistik.
    Improper use of the ordinary least-squares estimator in the switching regression-model1984Inngår i: Communications in Statistics - Theory and Methods, ISSN 0361-0926, E-ISSN 1532-415X, Vol. 13, nr 14, s. 1781-1791Artikkel i tidsskrift (Fagfellevurdert)
  • 7.
    Cronie, Ottmar
    et al.
    Stochastics, CWI, Amsterdam, The Netherlands.
    Yu, Jun
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för matematik och matematisk statistik.
    The discretely observed immigration-death process: Likelihood inference and spatiotemporal applications2016Inngår i: Communications in Statistics - Theory and Methods, ISSN 0361-0926, E-ISSN 1532-415X, Vol. 45, nr 18, s. 5279-5298Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    We consider a stochastic process, the homogeneous spatial immigration-death (HSID) process, which is a spatial birth-death process with as building blocks (i) an immigration-death (ID) process (a continuous-time Markov chain) and (ii) a probability distribution assigning iid spatial locations to all events. For the ID process, we derive the likelihood function, reduce the likelihood estimation problem to one dimension, and prove consistency and asymptotic normality for the maximum likelihood estimators (MLEs) under a discrete sampling scheme. We additionally prove consistency for the MLEs of HSID processes. In connection to the growth-interaction process, which has a HSID process as basis, we also fit HSID processes to Scots pine data.

  • 8. De Gooijer, JG
    et al.
    Brännäs, Kurt
    Umeå universitet, Samhällsvetenskapliga fakulteten, Handelshögskolan vid Umeå universitet, Nationalekonomi.
    Invertibility of nonlinear time-series models1995Inngår i: Communications in Statistics - Theory and Methods, ISSN 0361-0926, E-ISSN 1532-415X, Vol. 24, nr 11, s. 2701-2714Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Sufficient conditions for invertibility of non-linear time series models are available in the literature only for a few special cases. In this paper a practical and general method for checking invertibility is presented. Briefly stated, it consists of feeding independent and identically distributed innovations into the non-linear model and then observing whether the model blows up or not. Using this idea invertibility conditions are derived for several recently proposed non-linear moving average models. Finally, the method is applied to a number of bilinear models fitted to economic time series.

  • 9.
    Ekström, Magnus
    Department of Forest Resource Management and Geomatics, Swedish University of Agricultural Sciences, Umeå.
    Nonparametric estimation of the variance of sample means based on nonstationary spatial data2002Inngår i: Communications in Statistics - Theory and Methods, ISSN 0361-0926, E-ISSN 1532-415X, Vol. 31, nr 10, s. 1743-1775Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    In Politis and Romano (Politis, D.N.; Romano, J.P. Nonparametric Resampling for Homogeneous Strong Mixing Random Fields. Journal of Multivariate Analysis 1993, 47, 301–328.), different block resampling estimators of variance of general linear statistics, e.g., a sample mean, were proposed under the assumption of stationarity. In the present paper such estimators of variance of sample means, computed from nonstationary spatially indexed data , where is a finite subset of the integer lattice , are studied. Consistency of estimators of variance will be shown for the following kind of data: Observations taken from different lattice points are allowed to come from different distributions, and the dependence structure is allowed to differ over the lattice. We assume that all observed values are from distributions with the same expected value, or with expected values that decompose additively into directional components. Furthermore, it will be assumed that observations separated by a certain distance are independent.

  • 10.
    Forchini, Giovanni
    et al.
    Umeå universitet, Samhällsvetenskapliga fakulteten, Handelshögskolan vid Umeå universitet, Nationalekonomi.
    Peng, Bin
    Modified first-difference estimator in a panel data model with unobservable factors both in the errors and the regressors when the time dimension is small2017Inngår i: Communications in Statistics - Theory and Methods, ISSN 0361-0926, E-ISSN 1532-415X, Vol. 46, nr 24, s. 12226-12239Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Panel data models with factor structures in both the errors and the regressors have received considerable attention recently. In these models, the errors and the regressors are correlated and the standard estimators are inconsistent. This paper shows that, for such models, a modified first-difference estimator (in which the time and the cross-sectional dimensions are interchanged) is consistent as the cross-sectional dimension grows but the time dimension is small. Although the estimator has a non standard asymptotic distribution, t and F tests have standard asymptotic distribution under the null hypothesis.

  • 11.
    Källberg, David
    et al.
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för matematik och matematisk statistik.
    Seleznjev, Oleg
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för matematik och matematisk statistik.
    Estimation of entropy-type integral functionals2016Inngår i: Communications in Statistics - Theory and Methods, ISSN 0361-0926, E-ISSN 1532-415X, Vol. 45, nr 4, s. 887-905Artikkel i tidsskrift (Annet vitenskapelig)
    Abstract [en]

    Entropy-type integral functionals of densities are widely used in mathematical statistics, information theory, and computer science. Examples include measures of closeness between distributions (e.g., density power divergence) and uncertainty characteristics for a random variable (e.g., Renyi entropy). In this paper, we study U-statistic estimators for a class of such functionals. The estimators are based on ε-close vector observations in the corresponding independent and identically distributed samples. We prove asymptotic properties of the estimators (consistency and asymptotic normality) under mild integrability and smoothness conditions for the densities. The results can be applied in diverse problems in mathematical statistics and computer science (e.g., distribution identication problems, approximate matching for random databases, two-sample problems).

  • 12.
    Laukaityte, Inga
    et al.
    Umeå universitet, Samhällsvetenskapliga fakulteten, Handelshögskolan vid Umeå universitet, Statistik.
    Wiberg, Marie
    Umeå universitet, Samhällsvetenskapliga fakulteten, Handelshögskolan vid Umeå universitet, Statistik.
    Importance of sampling weights in multilevel modeling of international large-scale assessment data2018Inngår i: Communications in Statistics - Theory and Methods, ISSN 0361-0926, E-ISSN 1532-415X, Vol. 47, nr 20, s. 4991-5012Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Multilevel modeling is an important tool for analyzing large-scale assessment data. However, the standard multilevel modeling will typically give biased results for such complex survey data. This bias can be eliminated by introducing design weights which must be used carefully as they can affect the results. The aim of this paper is to examine different approaches and to give recommendations concerning handling design weights in multilevel models when analyzing large-scale assessments such as TIMSS (The Trends in International Mathematics and Science Study). To achieve the goal of the paper, we examined real data from two countries and included a simulation study. The analyses in the empirical study showed that using no weights or only level 1 weights sometimes could lead to misleading conclusions. The simulation study only showed small differences in estimation of the weighted and unweighted models when informative design weights were used. The use of unscaled or not rescaled weights however caused significant differences in some parameter estimates.

  • 13.
    Laukaityte, Inga
    et al.
    Umeå universitet, Samhällsvetenskapliga fakulteten, Handelshögskolan vid Umeå universitet, Statistik.
    Wiberg, Marie
    Umeå universitet, Samhällsvetenskapliga fakulteten, Handelshögskolan vid Umeå universitet, Statistik.
    Using plausible values in secondary analysis in large–scale assessments2017Inngår i: Communications in Statistics - Theory and Methods, ISSN 0361-0926, E-ISSN 1532-415X, Vol. 46, nr 22, s. 11341-11357Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Plausible values are typically used in large–scale assessment studies, in particular in the Trends in International Mathematics and Science Study and the Programme for International Student Assessment. Despite its large spread there are still some questions regarding the use of plausible values and how such use affects statistical analyses. The aim of this paper is to demonstrate the role of plausible values in large–scale assessment surveys when multilevel modelling is used. Different user strategies concerning plausible values for multilevel models as well as means and variances are examined. The results show that some commonly used user strategies give incorrect results while others give reasonable estimates but incorrect standard errors. These findings are important for anyone wishing to make secondary analyses of large–scale assessment data, especially those interested in using multilevel models to analyze the data.

  • 14.
    Lindkvist, Håkan
    et al.
    Center of Biostatistics, Department of Forest Resource Management and Geomatics, Swedish University of Agricultural Sciences , Umeå, Sweden.
    Belyaev, Yuri K
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för matematik och matematisk statistik.
    Asymptotic properties of estimators in a model of life data with warnings2004Inngår i: Communications in Statistics - Theory and Methods, ISSN 0361-0926, E-ISSN 1532-415X, Vol. 34, nr 2, s. 461-474Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    We consider a model where elements of a single type are life tested. All elements are observed up to the time of their failures or censorings. Three types of events are possible to observe during life testing for each element: failure, censoring, and warning, where a warning can only be observed before a failure or before censoring has occurred. It is essential to know if warnings influence subsequent failures. Two subsets of data are simultaneously considered: the first consisting of only the times of the first occurrences of failure, censoring, or warning, and the second consisting of the times for those elements where warnings occurred before failures or censorings. The first subset belongs to the competing risks model, and the second consists of left-truncated data. Estimators of the cumulative hazard function before and after warnings are derived and proved to be consistent, with asymptotic normal distributions. A null hypothesis where the cumulative hazard functions before and after warnings are proportional and a corresponding alternative hypothesis that they are not proportional are defined. Under this null hypothesis an estimator for the constant of proportionality is derived and showed to be strongly consistent. Martingale techniques are used and numerical examples are provided.

  • 15.
    Mukherjee, Amitava
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för matematik och matematisk statistik.
    Semi-Sequential One-Shot Monitoring of Small Disorders With Controlled Type I Error Rate2010Inngår i: Communications in Statistics - Theory and Methods, ISSN 0361-0926, E-ISSN 1532-415X, Vol. 39, nr 15, s. 2829-2847, artikkel-id PII 924854429Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    We propose a simple two-stage monitoring rule for detecting small disorders in a two-sample location problem. The proposed rule is based on ranks and hence is nonparametric in nature. In the first stage, we use a sequential monitoring scheme to decide the necessity of employing a location test at some point of time. If there is urgency, we simply use a two-sample Wilcoxon rank sum test in the second stage. This leads to a semi sequential one-shot monitoring procedure. We study some asymptotic performance of the proposed rule. We also present some numerical findings obtained through Monte Carlo studies. The proposed rule meets the challenge of controlling type I error rate in sequential monitoring of an incoming series of observations.

  • 16.
    quoreshi, AMM Shahiduzzaman
    Umeå universitet, Samhällsvetenskaplig fakultet, Nationalekonomi.
    Bivariate time series modelling of financial count data2006Inngår i: Communications in Statistics - Theory and Methods, ISSN 0361-0926, E-ISSN 1532-415X, Vol. 35, s. 1343-1358Artikkel i tidsskrift (Fagfellevurdert)
  • 17.
    Segerstedt, Bo
    Umeå universitet, Samhällsvetenskapliga fakulteten, Statistiska institutionen.
    On ordinary ridge regression in generalized linear models1992Inngår i: Communications in Statistics - Theory and Methods, ISSN 0361-0926, E-ISSN 1532-415X, ISSN 0361-0926, Vol. 21, nr 8, s. 2227-2246Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    In this paper it is shown that an ill-conditioned data matrix has similar effects on the parameter estimator when estimating generalized linear models as when estimating linear regression models. Asymptotically, the average length of the maximum likelihood estimator of a parameter vector increases as the conditioning of the covariance matrix deteriorates. A generalization of the ridge regression is suggested for maximum likelihood estimation in generalized linear models. In particular the existence of a ridge coefficient, k, such that the asymptotic mean square error of the generalized linear model ridge estimator is smaller than the asymptotic variance of the maximum likelihood estimator is shown. A numerical example illustrates the theoretical results

  • 18.
    Yu, Jun
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Matematisk statistik.
    Uniform convergence rates for a nearest neighbor density estimator under dependence assumptions1997Inngår i: Communications in Statistics - Theory and Methods, ISSN 0361-0926, E-ISSN 1532-415X, Vol. 26, nr 3, s. 601-616Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    In this paper the rates of strong uniform convergence over any compact set for an alternative nearest neighbor density estimator are obtained when the observations satisfy a ø-mixing or an a-mixing condition. In the ø-mixing case we obtain a quite better convergence rate than for a-mixing processes and we do not require a geometric condition on the mixing coefficients. For independent or m-dependent observations, as a special case of ømixing, the result gives us the optimal rate of strong uniform convergence for density estimators.

  • 19.
    Zhou, Zhiyong
    et al.
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för matematik och matematisk statistik.
    Yu, Jun
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för matematik och matematisk statistik.
    Adaptive estimation for varying coefficient modelswith nonstationary covariates2019Inngår i: Communications in Statistics - Theory and Methods, ISSN 0361-0926, E-ISSN 1532-415X, Vol. 48, nr 16, s. 4034-4050Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    In this paper, the adaptive estimation for varying coefficient models proposed by Chen, Wang, and Yao (2015) is extended to allowing for nonstationary covariates. The asymptotic properties of the estimator are obtained, showing different convergence rates for the integrated covariates and stationary covariates. The nonparametric estimator of the functional coefficient with integrated covariates has a faster convergence rate than the estimator with stationary covariates, and its asymptotic distribution is mixed normal. Moreover, the adaptive estimation is more efficient than the least square estimation for non normal errors. A simulation study is conducted to illustrate our theoretical results.

  • 20.
    Zhou, Zhiyong
    et al.
    Department of Mathematics, Zhejiang University, Hangzhou, China.
    Zhengyan, Lin
    Department of Mathematics, Zhejiang University, Hangzhou, China.
    Limit theory for random coefficient autoregressive process under possibly infinite variance error sequence2016Inngår i: Communications in Statistics - Theory and Methods, ISSN 0361-0926, E-ISSN 1532-415X, Vol. 45, nr 12, s. 3562-3576Artikkel i tidsskrift (Fagfellevurdert)
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