Seminal Ideas and Controversies in Statistics

von

Little, Roderick J. A.

BuchGebunden

Verkaufsrang16667inMathematik

CHF228.00

Jetzt vorbestellen

Beschreibung

Statistics has developed as a field through seminal ideas and fascinating controversies. This book concerns a wide-ranging set of 13 important statistical topics, grouped into three general areas:

Weitere Beschreibungen

Details

ISBN/GTIN978-1-032-49717-4

ProduktartBuch

EinbandGebunden

VerlagTaylor and FrancisChapman and Hall/CRC

Erscheinungsdatum25.02.2025

Auflage1. A.

ReiheChapman & Hall/CRC Monographs on Statistics and Applied Probability

Seiten216 Seiten

SpracheEnglisch

MasseBreite 156 mm, Höhe 234 mm

IllustrationenFarb., s/w. Abb.

Artikel-Nr.52093716

KatalogBuchzentrum

Datenquelle-Nr.47573343

WarengruppeMathematik

Weitere Details

Reihe

Multivariate Geostatistical Models

Density Estimation for Statistics and Data Analysis

Transformation and Weighting in Regression

Analysis of Infectious Disease Data

Inspection Errors for Attributes in Quality Control

Nonparametric Regression and Generalized Linear Models

Differential Geometry and Statistics

Networks and Chaos - Statistical and Probabilistic Aspects

Practical Risk Theory for Actuaries

Number-Theoretic Methods in Statistics

An Introduction to the Bootstrap

Statistics for Long-Memory Processes

Cyclic and Computer Generated Designs

Nonlinear Models for Repeated Measurement Data

Distribution-Free Statistical Methods, Second Edition

Local Polynomial Modelling and Its Applications

Analysis of Incomplete Multivariate Data

Statistical Aspects of BSE and vCJD

The Theory of the Design of Experiments

Analysis of Time Series Structure

Statistics in the 21st Century

Subset Selection in Regression

Statistical Inference and Simulation for Spatial Point Processes

Diagnostic Checks in Time Series

Measurement Error in Nonlinear Models

Missing Data in Longitudinal Studies

Antedependence Models for Longitudinal Data

Circular and Linear Regression

Expansions and Asymptotics for Statistics

Simultaneous Inference in Regression

Robust Nonparametric Statistical Methods

Extreme Value Methods with Applications to Finance

Maximum Likelihood Estimation for Sample Surveys

Constrained Principal Component Analysis and Related Techniques

Statistical Analysis of Spatial and Spatio-Temporal Point Patterns

Analysis of Variance for Functional Data

Quasi-Least Squares Regression

Robust Cluster Analysis and Variable Selection

Hierarchical Modeling and Analysis for Spatial Data

Design and Analysis of Cross-Over Trials

Data Analysis and Approximate Models

Models for Dependent Time Series

Stochastic Analysis for Gaussian Random Processes and Fields

Statistical Learning with Sparsity

Bayesian Inference for Partially Identified Models

Measuring Statistical Evidence Using Relative Belief

State-Space Methods for Time Series Analysis

Multi-State Survival Models for Interval-Censored Data

Simultaneous Inference in Regression

Antedependence Models for Longitudinal Data

Generalized Linear Models with Random Effects

Sufficient Dimension Reduction

Probabilistic Foundations of Statistical Network Analysis

Multivariate Kernel Smoothing and Its Applications

Nonparametric Models for Longitudinal Data

Large Covariance and Autocovariance Matrices

Multistate Models for the Analysis of Life History Data

The Statistical Analysis of Multivariate Failure Time Data

Martingale Methods in Statistics

Propensity Score Modeling and Adjustment Procedures

Replication and Evidence Factors in Observational Studies

Measuring Statistical Evidence Using Relative Belief

Generalized Linear Models with Random Effects

Sequential Change Detection and Hypothesis Testing

Asymptotic Analysis of Mixed Effects Models

Über den/die AutorIn

Little, Roderick J. A.

Roderick J. A. Little is Richard D. Remington Distinguished University Professor Emeritus at the University of Michigan, where he also holds emeritus appointments in the Department of Statistics and the Institute for Social Research. After secondary school at Glasgow Academy, he received a B.A. in Mathematics from Gonville and Caius College, Cambridge University, and M.Sc. and Ph.D. degrees in Statistics from the Imperial College of Science and Technology, London University. Professor Little is a pioneer and thought leader in the fields of statistical analysis with missing data, Bayesian inference in sample surveys and causal inference. He has received some of the highest honors in statistics and science, including being elected to the U.S. National Academy of Medicine and American Academy of Arts and Sciences.

Seminal Ideas and Controversies in Statistics

Beschreibung

Details

Reihe

Über den/die AutorIn

Weitere Produkte von Little, Roderick J. A.