Entdecke #BookTok

044 209 91 25 079 869 90 44

Die Merkliste ist leer.

Der Warenkorb ist leer.

Kostenloser Versand möglich

Registrieren Passwort vergessen?

Kostenloser Versand möglich

Bitte warten - die Druckansicht der Seite wird vorbereitet.

Der Druckdialog öffnet sich, sobald die Seite vollständig geladen wurde.
Sollte die Druckvorschau unvollständig sein, bitte schliessen und "Erneut drucken" wählen.

Druckansicht verlassenErneut drucken

Sampling Algorithms

Sampling Algorithms

ISBN/GTIN

Sampling Algorithms

von

BuchGebunden

Verkaufsrang23947inNaturwissenschaft und Technik

CHF152.00

BuchabCHF152.00

E-BookCHF130.00

In den Warenkorb

Beschreibung

Over the last few decades, important progresses in the methods of sampling have been achieved. This book draws up an inventory of new methods that can be useful for selecting samples. Forty-six sampling methods are described in the framework of general theory. The algorithms are described rigorously, which allows implementing directly the described methods. This book is aimed at experienced statisticians who are familiar with the theory of survey sampling.

Weitere Beschreibungen

Details

ISBN/GTIN978-0-387-30814-2

ProduktartBuch

EinbandGebunden

VerlagSpringer Nature ENSpringer

Erscheinungsdatum28.03.2006

ReiheSpringer Series in Statistics

Seiten216 Seiten

SpracheEnglisch

MasseBreite 155 mm, Höhe 235 mm

Gewicht1120 g

Artikel-Nr.3770271

KatalogBuchzentrum

Datenquelle-Nr.2201039

WarengruppeNaturwissenschaft und Technik

Weitere Details

Reihe

Statistical Decision Theory and Bayesian Analysis

Asymptotic Methods in Statistical Decision Theory

Goodness-Of-Fit Statistics for Discrete Multivariate Data

Smoothing Techniques

Time Series: Theory and Methods

The Bootstrap and Edgeworth Expansion

Theory of Statistics

The Jackknife and Bootstrap

The Bootstrap and Edgeworth Expansion

Statistical Models Based on Counting Processes

Advanced Statistics

The Statistical Theory of Shape

Smoothing Methods in Statistics

Tools for Statistical Inference

Nonparametric Smoothing and Lack-Of-Fit Tests

Bayesian Forecasting and Dynamic Models

Arch Models and Financial Applications

Quasi-Likelihood and Its Application

Exponential Families of Stochastic Processes

Fitting Linear Relationships

Conditional Specification of Statistical Models

Orthogonal Arrays

Gaussian and Non-Gaussian Linear Time Series and Random Fields

Statistical Methods in Software Engineering

Nonparametric Curve Estimation

Interpolation of Spatial Data

Subsampling

Monte Carlo Methods in Bayesian Computation

Asymptotics in Statistics

Robust Diagnostic Regression Analysis

Asymptotic Theory of Statistical Inference for Time Series

Linear Mixed Models for Longitudinal Data

Combinatorial Methods in Density Estimation

Chaos: A Statistical Perspective

Multivariate Statistical Modelling Based on Generalized Linear Models

Bayesian Survival Analysis

Scan Statistics

A Distribution-Free Theory of Nonparametric Regression

Observational Studies

Statistical Tools for Nonlinear Regression

Resampling Methods for Dependent Data

Elements of Multivariate Time Series Analysis

Model Assisted Survey Sampling

Bayesian Nonparametrics

Partial Identification of Probability Distributions

Permutation, Parametric, and Bootstrap Tests of Hypotheses

Exploring Multivariate Data with the Forward Search

Nonparametric and Semiparametric Models

Inference in Hidden Markov Models

Modern Multidimensional Scaling

Statistical Demography and Forecasting

Functional Data Analysis

Nonlinear Time Series

Nonparametric Functional Data Analysis

Sampling Algorithms

Non-Negative Matrices and Markov Chains

Semiparametric Theory and Missing Data

Model-based Geostatistics

Life Distributions

Linear and Generalized Linear Mixed Models and Their Applications

Permutation Methods

Indirect Sampling

Correlated Data Analysis: Modeling, Analytics, and Applications

Information Criteria and Statistical Modeling

Multiscale Modeling

Linear Models and Generalizations

Multiple Testing Procedures with Applications to Genomics

Simulation and Inference for Stochastic Differential Equations

Statistical Decision Theory

Introduction to Empirical Processes and Semiparametric Inference

Bayesian Reliability

Statistical Learning from a Regression Perspective

Introduction to Nonparametric Estimation

The Elements of Statistical Learning

Statistical Analysis of Network Data

Maximum Penalized Likelihood Estimation

Time Series: Theory and Methods

Monte Carlo and Quasi-Monte Carlo Sampling

Resampling Methods for Dependent Data

Introduction to Rare Event Simulation

Life Distributions

Models for Discrete Longitudinal Data

Nonparametric Functional Data Analysis

Semiparametric Theory and Missing Data

Model-Based Geostatistics

Finite Mixture and Markov Switching Models

Inference in Hidden Markov Models

Exploring Multivariate Data with the Forward Search

Multiple Testing Procedures with Applications to Genomics

Multiscale Modeling

Statistical Decision Theory

Introduction to Empirical Processes and Semiparametric Inference

Simulation and Inference for Stochastic Differential Equations

Bayesian Reliability

Regression Modeling Strategies

Maximum Penalized Likelihood Estimation

Bayesian Survival Analysis

Sample Survey Theory

The Design and Analysis of Computer Experiments

A Distribution-Free Theory of Nonparametric Regression

Über den/die AutorIn

Yves Tillé is a professor at the University of Neuchatel (Switzerland).

Weitere Produkte von Tillé, Yves

Sampling Methods

Sampling Methods

Théorie des sondages : 2e édition

Sampling and Estimation from Finite Populations

Sampling and Estimation from Finite Populations

Sampling and Estimation from Finite Populations