000 -Record Label |
fixed length control field |
02949nam a22002895i 4500 |
005 - Identificador da versão |
control field |
20200214170452.0 |
010 ## - ISBN - International Standard Book Number |
Número (ISBN) |
978-0-387-92710-7 |
Modalidade de aquisição e/ou preço |
compra |
100 ## - Entrada principal |
Dados gerais de processamento |
20150401d2010 k||y0pory50 ba |
101 ## - Língua do documento |
Língua do texto, banda sonora, etc. |
eng |
102 ## - País da publicação |
País de publicação |
US - United States of America |
200 ## - Título |
Título próprio |
Comparing distributions |
Indicação geral da natureza do documento |
Documento eletrónico |
Primeira menção de responsabilidade |
Olivier Thas |
210 ## - Local de edição |
Lugar da edição, distribuição, etc. |
New York, |
Nome do editor, distribuidor, etc. |
Springer |
Data da publicação, distribuição, etc. |
2010 |
215 ## - Descrição física (Vol.pg.fl.tm.fsc) |
Descrição física |
XVI, 354 p. |
225 ## - Coleção |
Título próprio da colecção |
Springer Series in Statistics |
300 ## - Notas gerais |
Texto da nota |
Colocação: Online |
303 ## - Notas Informação descritiva |
Texto da nota |
Comparing Distributions refers to the statistical data analysis that encompasses the traditional goodness-of-fit testing. Whereas the latter includes only formal statistical hypothesis tests for the one-sample and the K-sample problems, this book presents a more general and informative treatment by also considering graphical and estimation methods. A procedure is said to be informative when it provides information on the reason for rejecting the null hypothesis. Despite the historically seemingly different development of methods, this book emphasises the similarities between the methods by linking them to a common theory backbone. This book consists of two parts. In the first part statistical methods for the one-sample problem are discussed. The second part of the book treats the K-sample problem. Many sections of this second part of the book may be of interest to every statistician who is involved in comparative studies. The book gives a self-contained theoretical treatment of a wide range of goodness-of-fit methods, including graphical methods, hypothesis tests, model selection and density estimation. It relies on parametric, semiparametric and nonparametric theory, which is kept at an intermediate level; the intuition and heuristics behind the methods are usually provided as well. The book contains many data examples that are analysed with the cd R-package that is written by the author. All examples include the R-code. Because many methods described in this book belong to the basic toolbox of almost every statistician, the book should be of interest to a wide audience. In particular, the book may be useful for researchers, graduate students and PhD students who need a starting point for doing research in the area of goodness-of-fit testing. Practitioners and applied statisticians may also be interested because of the many examples, the R-code and the stress on the informative nature of the procedures. Olivier Thas is Associate Professor of Biostatistics at Ghent University. He has published methodological papers on goodness-of-fit testing, but he has also published more applied work in the areas of environmental statistics and genomics. |
606 ## - Nome comum como assunto |
Koha Internal code |
6798 |
Elemento de entrada |
Distribuição (Teoria das probabilidades) |
680 ## - Classificação Biblioteca Congresso |
Notação |
QA273.6 |
700 ## - Autor (resp. principal) |
Palavra de ordem |
Thas |
Outra parte do nome |
Olivier |
Koha Internal Code |
19076 |
801 ## - Fonte de origem |
País |
Portugal |
Regras de catalogação |
RPC |
856 ## - URL Endereço WEB |
URL |
http://dx.doi.org/10.1007/978-0-387-92710-7 |
942 ## - Elementos de entrada adicionados (Koha) |
Fonte da classificação ou esquema de estante |
|
Tipo de item no Koha |
E-Books |
Suprimido |
0 |