1.

Record Nr.

UNINA9910454541803321

Autore

Tiku Moti Lal

Titolo

Robust estimation and hypothesis testing [[electronic resource] /] / Moti L. Tiku, Aysen D. Akkaya

Pubbl/distr/stampa

New Delhi, : New Age International (P) Ltd., Publishers, 2004

ISBN

1-281-89246-7

9786611892463

81-224-2537-2

Descrizione fisica

1 online resource (354 p.)

Altri autori (Persone)

AkkayaAysen D

Disciplina

519.5/44

Soggetti

Robust statistics

Nonparametric statistics

Estimation theory

Electronic books.

Lingua di pubblicazione

Inglese

Formato

Materiale a stampa

Livello bibliografico

Monografia

Note generali

Description based upon print version of record.

Nota di bibliografia

Includes bibliographical references (p. 308-330) and index.

Nota di contenuto

Cover; Preface; Contents; Chapter 1 Robustness of Some Classical Estimators and Tests; Chapter 2 Estimation of Location and Scale Parameters; Chapter 3 Linear Regression with Normal and Non-normal Error Distributions; Chapter 4 Binary Regression with Logistic and Nonlogistic Density Functions; Chapter 5 Autoregressive Models in Normal and Non-Normal Situations; Chapter 6 Analysis of Variance in Experimental Design; Chapter 7 Censored Samples from Normal and Non-Normal Distributions; Chapter 8 Robustness of Estimators and Tests; Chapter 9 Goodness-of-fit and Detection of Outliers

Chapter 10 Estimation in Sample SurveyChapter 11 Applications; Bibliography; Index

Sommario/riassunto

In statistical theory and practice, a certain distribution is usually assumed and then optimal solutions sought. Since deviations from an assumed distribution are very common, one cannot feel comfortable with assuming a particular distribution and believing it to be exactly correct. That brings the robustness issue in focus. In this book, we have given statistical procedures which are robust to plausible deviations from an assumed mode. The method of modified maximum



likelihood estimation is used in formulating these procedures. The modified maximum likelihood estimators are explicit functions