The Experts below are selected from a list of 321 Experts worldwide ranked by ideXlab platform
Teemu Roos - One of the best experts on this subject based on the ideXlab platform.
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Subset Selection in Linear Regression using Sequentially Normalized Least Squares: Asymptotic Theory
Scandinavian Journal of Statistics, 2015Co-Authors: Jussi Määttä, Daniel F. Schmidt, Teemu RoosAbstract:This article examines the recently proposed sequentially normalized least squares criterion for the linear regression subset selection problem. A simplified formula for computation of the criterion is presented, and an expression for its Asymptotic form is derived without the assumption of normally distributed errors. Asymptotic Consistency is proved in two senses: (i) in the usual sense, where the sample size tends to infinity, and (ii) in a non-standard sense, where the sample size is fixed and the noise variance tends to zero.
Chao A. Hsiung - One of the best experts on this subject based on the ideXlab platform.
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Goodness‐of‐fit Tests for Semi‐Markov and Markov Survival Models with One Intermediate State
Scandinavian Journal of Statistics, 2001Co-Authors: I-shou Chang, Yuan-chuan Chuang, Chao A. HsiungAbstract:Survival data with one intermediate state are described by semi-Markov and Markov models for counting processes whose intensities are defined in terms of two stopping times T 1 < T 2 , Problems of goodness-of-fit for these models are studied. The test statistics are proposed by comparing Nelson-Aalen estimators for data stratified according to T 1 . Asymptotic distributions of these statistics are established in terms of the weak convergence of some random fields. Asymptotic Consistency of these test statistics is also established. Simulation studies are included to indicate their numerical performance.
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Asymptotic Consistency of the Maximum Likelihood Estimate in Positron Emission Tomography and Applications
The Annals of Statistics, 1994Co-Authors: I-shou Chang, Chao A. HsiungAbstract:This paper indicates that a minor modification of the maximum likelihood estimate of Vardi, Shepp and Kaufman can be regarded as a step in the standard nonparametric MLE by the method of sieves and establishes the Asymptotic Consistency for it. This method of sieves suggests that the number of pixels needs to be in line with the number of detectors in order to avoid poor image reconstructions. A simulation study is also presented to support this suggestion
Dimitris N. Politis - One of the best experts on this subject based on the ideXlab platform.
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A GENERALIZED BLOCK BOOTSTRAP FOR SEASONAL TIME SERIES
Journal of Time Series Analysis, 2013Co-Authors: Anna E. Dudek, Efstathios Paparoditis, Jacek Leśkow, Dimitris N. PolitisAbstract:When time-series data contain a periodic/seasonal component, the usual block bootstrap procedures are not directly applicable. We propose a modification of the block bootstrap – the generalized seasonal block bootstrap (GSBB) – and show its Asymptotic Consistency without undue restrictions on the relative size of the period and block size. Notably, it is exactly such restrictions that limit the applicability of other proposals of block bootstrap methods for time series with periodicities. The finite-sample performance of the GSBB is also illustrated by means of a small simulation experiment.
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Local block bootstrap inference for trending time series
Metrika, 2013Co-Authors: Arif Dowla, Efstathios Paparoditis, Dimitris N. PolitisAbstract:Resampling for stationary sequences has been well studied in the last couple of decades. In the paper at hand, we focus on nonstationary time series data where the nonstationarity is due to a slowly-changing deterministic trend. We show that the local block bootstrap methodology is appropriate for inference under this locally stationary setting without the need of detrending the data. We prove the Asymptotic Consistency of the local block bootstrap in the smooth trend model, and complement the theoretical results by a finite-sample simulation.
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Testing Time Series Linearity: Traditional and Bootstrap Methods
Time Series Analysis: Methods and Applications, 2012Co-Authors: Arthur Berg, Timothy L. Mcmurry, Dimitris N. PolitisAbstract:Abstract We review the notion of time series linearity and describe recent advances in linearity and Gaussianity testing via data resampling methodologies. Many advances have been made since the first published tests of linearity and Gaussianity by Subba Rao and Gabr in 1980, including several resampling-based proposals. This chapter is intended to be instructive in explaining and motivating linearity testing. Recent results on the validity of the AR-sieve bootstrap for linearity testing are reviewed. In addition, a subsampling-based linearity and Gaussianity test is proposed where Asymptotic Consistency of the testing procedure is justified.
Kesar Singh - One of the best experts on this subject based on the ideXlab platform.
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Balanced Confidence Regions Based on Tukey’s Depth and the Bootstrap
Journal of the Royal Statistical Society: Series B (Statistical Methodology), 1997Co-Authors: Arthur B. Yeh, Kesar SinghAbstract:SUMMARY We propose and study the bootstrap confidence regions for multivariate parameters based on Tukey's depth. The bootstrap is based on the normalized or Studentized statistic formed from an independent and identically distributed random sample obtained from some unknown distribution in Rq. The bootstrap points are deleted on the basis of Tukey's depth until the desired confidence level is reached. The proposed confidence regions are shown to be second order balanced in the context discussed by Beran. We also study the Asymptotic Consistency of Tukey's depth-based bootstrap confidence regions. The applicability of the method proposed is demonstrated in a simulation study.
Hamed Zakerzadeh - One of the best experts on this subject based on the ideXlab platform.
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Asymptotic Consistency of the RS-IMEX Scheme for the Low-Froude Shallow Water Equations: Analysis and Numerics
Theory Numerics and Applications of Hyperbolic Problems II, 2018Co-Authors: Hamed ZakerzadehAbstract:In the present work, we formally prove the Asymptotic Consistency of the recently presented Reference Solution IMplicit–EXplicit (RS-IMEX) scheme for the two-dimensional shallow water equations. The scheme has been analyzed extensively for the low-Froude one-dimensional shallow water equations in (Zakerzadeh IGPM report 455 (2016) [18]), and the present paper is going to discuss the Asymptotic Consistency analysis for the two-dimensional case, with the aid of some numerical experiments.
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The RS-IMEX scheme for the rotating shallow water equations with the Coriolis force
Springer Proceedings in Mathematics & Statistics, 2017Co-Authors: Hamed ZakerzadehAbstract:In this note , we comment on the applicability of the recently-presented RS-IMEX scheme for the rotating shallow water equations. We show the Asymptotic Consistency of the scheme for the quasi-geostrophic distinguished limit. We also test the quality of the computed solution by a numerical example.
