Описание: This is a history of parametric statistical inference, written by one of the most important historians of statistics of the 20th century, Anders Hald. This book can be viewed as a follow-up to his two most recent books, although this current text is much more streamlined and contains new analysis of many ideas and developments. And unlike his other books, which were encyclopedic by nature, this book can be used for a course on the topic, the only prerequisites being a basic course in probability and statistics.The book is divided into five main sections:* Binomial statistical inference;* Statistical inference by inverse probability;* The central limit theorem and linear minimum variance estimation by Laplace and Gauss;* Error theory, skew distributions, correlation, sampling distributions;* The Fisherian Revolution, 1912-1935.Throughout each of the chapters, the author provides lively biographical sketches of many of the main characters, including Laplace, Gauss, Edgeworth, Fisher, and Karl Pearson. He also examines the roles played by DeMoivre, James Bernoulli, and Lagrange, and he provides an accessible exposition of the work of R.A. Fisher.This book will be of interest to statisticians, mathematicians, undergraduate and graduate students, and historians of science.
Автор: Ulhas Jayram Dixit Название: Examples in Parametric Inference with R ISBN: 9811008884 ISBN-13(EAN): 9789811008887 Издательство: Springer Рейтинг: Цена: 9362.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The book is divided into eight chapters: Chapter 1 provides an overview of topics on sufficiency and completeness, while Chapter 2 briefly discusses unbiased estimation. Chapter 6 discusses Bayes, while Chapter 7 studies some more powerful tests.
Описание: This book considers specific inferential issues arising from the analysis of dynamic shapes with the attempt to solve the problems at hand using probability models and nonparametric tests.
Описание: This book provides statistical methodologies for time series data, focusing on copula-based Markov chain models for serially correlated time series.
Автор: Cheng Russell C H Название: Non-Standard Parametric Statistical Inference ISBN: 0198505043 ISBN-13(EAN): 9780198505044 Издательство: Oxford Academ Рейтинг: Цена: 19404.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This research monograph gives a unified view of non-standard estimation problems. It provides an overall mathematical framework, but also draws together and studies in detail a large number of practical problems, previously only treated separately, offering solution methods and numerical procedures for each.
Описание: This proceedings volume contains eight selected papers thatwere presented in the International Symposium in Statistics (ISS) 2015 OnAdvances in Parametric and Semi-parametric Analysis of Multivariate, TimeSeries, Spatial-temporal, and Familial-longitudinal Data, held in St. John`s,Canada from July 6 to 8, 2015.
Chapter 1. The CUB models.- Chapter 2. Customer satisfaction heterogeneity.- Chapter 3. Ranking multivariate populations.- Chapter 4. Composite indicators and satisfaction profiles.- Chapter 5. Analyzing Survey Data Using Multivariate Rank-Based Inference
Автор: Ole E Barndorff-Nielsen Название: Parametric Statistical Models and Likelihood ISBN: 0387969284 ISBN-13(EAN): 9780387969282 Издательство: Springer Рейтинг: Цена: 16769.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: A few preliminaries 2 1. Likelihood and auxiliary statistics 1. Likelihood 4 1. Moments and cumulants of log likelihood derivatives 10 1. Marginal and conditional likelihood 15 * 1. Combinants, auxiliaries, and the p -model 19 1. Pseudo likelihood, profile likelihood and modified 30 profile likelihood 1.
Автор: Mayer Alvo; Philip L. H. Yu Название: A Parametric Approach to Nonparametric Statistics ISBN: 3030068048 ISBN-13(EAN): 9783030068042 Издательство: Springer Рейтинг: Цена: 8384.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book demonstrates that nonparametric statistics can be taught from a parametric point of view. As a result, one can exploit various parametric tools such as the use of the likelihood function, penalized likelihood and score functions to not only derive well-known tests but to also go beyond and make use of Bayesian methods to analyze ranking data. The book bridges the gap between parametric and nonparametric statistics and presents the best practices of the former while enjoying the robustness properties of the latter.This book can be used in a graduate course in nonparametrics, with parts being accessible to senior undergraduates. In addition, the book will be of wide interest to statisticians and researchers in applied fields.
Автор: E. Brodsky; B.S. Darkhovsky Название: Non-Parametric Statistical Diagnosis ISBN: 0792363280 ISBN-13(EAN): 9780792363286 Издательство: Springer Рейтинг: Цена: 15372.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: A systematic account of various problems of statistical diagnostics - in other words, the detection of changes in probabilistic characteristics of random processes and fields. Methods of solving such problems are proposed, based upon a unified non-parametric approach.
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