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Covariance Modelling

ISBN/GTIN

Covariance Modelling

von

MacKenzie, Gilbert

BuchGebunden

Verkaufsrang4653696in

CHF108.00

In den Warenkorb

Beschreibung

Written by a researcher at the forefront of the field, this book expounds on modern theory of covariance modelling in which regression models are used to model the covariance structure simultaneously with the mean. In a systematic treatment, quite possibly the first available in a convenient format, the author then compares the results obtained to conventional methods and delineates why the new methodology is advantageous using a series of classical examples taken from the existing literature.

Weitere Beschreibungen

Details

ISBN/GTIN978-1-58488-608-2

ProduktartBuch

EinbandGebunden

VerlagTaylor and FrancisChapman and Hall/CRC

Erscheinungsdatum01.07.2021

ReiheChapman & Hall/CRC Monographs on Statistics and Applied Probability

Seiten256 Seiten

SpracheEnglisch

MasseBreite 152 mm, Höhe 229 mm

IllustrationenFarb., s/w. Abb.

Artikel-Nr.37455423

KatalogBuchzentrum

Datenquelle-Nr.28238845

Weitere Details

Reihe

Covariance Modelling

Multivariate Geostatistical Models

Statistical Inference

Analysis of Survival Data

Density Estimation for Statistics and Data Analysis

Transformation and Weighting in Regression

Analysis of Infectious Disease Data

Analysis of Binary Data

Analysis of Repeated Measures

Inspection Errors for Attributes in Quality Control

Queues

Nonparametric Regression and Generalized Linear Models

Differential Geometry and Statistics

Markov Models & Optimization

Networks and Chaos - Statistical and Probabilistic Aspects

Practical Risk Theory for Actuaries

Number-Theoretic Methods in Statistics

Predictive Inference

Inference and Asymptotics

Kernel Smoothing

An Introduction to the Bootstrap

Statistics for Long-Memory Processes

Biplots

Cyclic and Computer Generated Designs

Nonlinear Models for Repeated Measurement Data

Distribution-Free Statistical Methods, Second Edition

Local Polynomial Modelling and Its Applications

Time Series Models

Multivariate Dependencies

Analysis of Incomplete Multivariate Data

Variance Components

Retrial Queues

Statistical Evidence

Stochastic Geometry

Classification

Statistical Aspects of BSE and vCJD

Set-Indexed Martingales

Algebraic Statistics

The Theory of the Design of Experiments

Analysis of Time Series Structure

Empirical Likelihood

Accelerated Life Models

Statistics in the 21st Century

Components of Variance

Subset Selection in Regression

Statistical Inference and Simulation for Spatial Point Processes

Diagnostic Checks in Time Series

Stereology for Statisticians

Gaussian Markov Random Fields

Measurement Error in Nonlinear Models

Nonlinear Time Series

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

Statistical Inference

Extreme Value Methods with Applications to Finance

Smoothing Splines

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

Sequential Analysis

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

Inferential Models

Models for Dependent Time Series

Pareto Distributions

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

Absolute Risk

Generalized Linear Models with Random Effects

Queues

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

Analysis of Repeated Measures

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

Object Oriented Data Analysis

Über den/die AutorIn

MacKenzie, Gilbert

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