Asymptotic and Methodological Statistics
Description
This book on asymptotic and methodological statistics celebrates the distinguished career of Marie Husková and her foundational work in modern mathematical statistics. It brings together original research contributions from renowned statisticians, focusing on asymptotic theory, methodological innovations, and applications in statistical inference. The volume highlights cutting-edge developments in change-point analysis, goodness-of-fit testing and nonparametric statistics, reflecting the extensive impact Marie Husková has had in shaping the direction of contemporary statistical science. It serves both as a tribute to her career and as a valuable resource for researchers and PhD students.
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Daniel Hlubinka is an Associate Professor at the Department of Probability and Mathematical Statistics, Faculty of Mathematics and Physics, Charles University in Prague, Czech Republic. His research interests include stochastic processes and functional data.
Sárka Hudecová is an Associate Professor at the Department of Probability and Mathematical Statistics, Faculty of Mathematics and Physics, Charles University in Prague, Czech Republic. Her research interests include time series analysis and multivariate statistics.
Matús Maciak is an Associate Professor at the Department of Probability and Mathematical Statistics, Faculty of Mathematics and Physics, Charles University in Prague, Czech Republic. His research interests include change point analysis and non-parametric statistics.
Michal Pesta is an Associate Professor at the Department of Probability and Mathematical Statistics, Faculty of Mathematics and Physics, Charles University in Prague, Czech Republic. His research interests include resampling methods and statistical inference.
Content
Marie Husková: Annotated Echoes (from 1968 to 2025) (Daniel Hlubinka, Sárka Hudecová, Matús Maciak, and Michal Pesta).- Part I Change Point Analysis.- 1 On Epidemic Change Point Detection Under Strong Mixing Conditions (István Berkes and Siegfried Hörmann).- 2 Change Point Analysis for Polynomial Trends in Functional Time Series (Rohit Gajendragadkar and Gregory Rice).- 3 A Model-free Test of the Time-reversibility of Climate Change Processes (Yuichi Goto and Marc Hallin).- 4 Detecting Changes in the Regression Parameter of AR(1) and RCA(1) Processes with Changing Errors (Lajos Horváth).- 5 Behavior of Pesta-Wendler Estimate of Change Point (Daniela Jarusková).- 6 Structural Break Tests in Dependent Functional Linear Models (Tianke Li and Alexander Aue).- 7 On the Use of ??-statistics in Change Point Testing (Claudia Kirch and Martin Wendler).- 8 Changepoint in Panel Data: CUSUM Statistics under Different Asymptotics (Matús Maciak).- 9 SVD-bootstrap for Detection of Tensor Changes (Barbora Pestová, Michal Pesta, and Martin Romanák).- 10 Detection Changes in a Linear Dynamic Panel Data Model (Zuzana Prásková).- 11 A Weighted Regression Approach to Break-Point Detection in Panel Data (Charl Pretorius and Heinrich Roodt).- 12 A Change or Not a Change - A Review on Some Joint Work with Marie Husková (Josef G. Steinebach).- 13 Some Non-asymptotic Rank Tests for Change Points in Regression (Silvelyn Zwanzig and Rauf Ahmad).- Part II Goodness-of-fit Testing.- 14 Specification Tests for the Error-Law in Vector Multiplicative Errors Models (Sárka Hudecová and Simos G. Meintanis).- 15 Mahalanobis Distance and General Linear Hypotheses in Linear Models (Paul Janssen, Luc Duchateau, and Noël Veraverbeke).- 16 Goodness-of-fit Testing for the Error Distribution in Functional Linear Models (Natalie Neumeyer and Leonie Selk).- Part III Nonparametric Statistics.- 17 Cartesian Statistics on Spheres (Rudolf Beran).- 18 Diagnostic Tools for Exploring Differences in Distributional Properties Between Two Samples: Nonparametric Approach (Bogdan Cmiel and Teresa Ledwina).- 19 Nonparametric Error Variance Estimation in Regression: A Review (Irène Gijbels).- 20 Outliers and Related Problems (Lev B. Klebanov, Jaromír Antoch, and Ashot V. Kakosyan).- 21 Maximum Likelihood Estimation of a General Mixing Distribution: Variations on Parametric Domains (Ivan Mizera).- 22 New Asymptotic Results for Bernstein Estimators for Conditional Copulas (Noël Veraverbeke).