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[null,"1.","Record Nr.",null,"UNINA9910454541803321"]
[null,null,"Autore",null,"Tiku Moti Lal"]
[null,null,"Titolo",null,"Robust estimation and hypothesis testing [[electronic resource] /] / Moti L. Tiku, Aysen D. Akkaya"]
[null,null,"Pubbl/distr/stampa",null,"New Delhi, : New Age International (P) Ltd., Publishers, 2004"]
[null,null,"ISBN",null,"1-281-89246-7"]
[{"$nulls":4},"9786611892463"]
[{"$nulls":4},"81-224-2537-2"]
[null,null,"Descrizione fisica",null,"1 online resource (354 p.)"]
[null,null,"Disciplina",null,"519.5/44"]
[null,null,"Soggetti",null,"Robust statistics"]
[{"$nulls":4},"Nonparametric statistics"]
[{"$nulls":4},"Estimation theory"]
[{"$nulls":4},"Electronic books."]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,null,"Note generali","Description based upon print version of record."]
[null,null,null,"Nota di bibliografia","Includes bibliographical references (p. 308-330) and index."]
[null,null,"Nota di contenuto",null,"Cover; Preface; Contents; Chapter 1 Robustness of Some Classical Estimators and Tests; Chapter 2 Estimation of Location and Scale Parameters; Chapter 3 Linear Regression with Normal and Non-normal Error Distributions; Chapter 4 Binary Regression with Logistic and Nonlogistic Density Functions; Chapter 5 Autoregressive Models in Normal and Non-Normal Situations; Chapter 6 Analysis of Variance in Experimental Design; Chapter 7 Censored Samples from Normal and Non-Normal Distributions; Chapter 8 Robustness of Estimators and Tests; Chapter 9 Goodness-of-fit and Detection of Outliers"]
[{"$nulls":4},"Chapter 10 Estimation in Sample SurveyChapter 11 Applications; Bibliography; Index"]
[null,null,null,"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"]