SPERLICH, Stefan and Jiří ZELINKA. Generalized Additive Models. In XploRe - Application Guide. Berlin: Springer, 2000, p. 171-220. ISBN 3-540-67545-0.
Other formats:   BibTeX LaTeX RIS
Basic information
Original name Generalized Additive Models
Authors SPERLICH, Stefan and Jiří ZELINKA (203 Czech Republic).
Edition Berlin, XploRe - Application Guide, p. 171-220, 2000.
Publisher Springer
Other information
Original language English
Type of outcome Chapter(s) of a specialized book
Field of Study 10103 Statistics and probability
Country of publisher Germany
Confidentiality degree is not subject to a state or trade secret
WWW URL
RIV identification code RIV/00216224:14310/00:00002870
Organization unit Faculty of Science
ISBN 3-540-67545-0
Keywords in English additive model; geberalized additive model; backfitting; XploRe; quantlet
Tags additive model, backfitting, geberalized additive model, quantlet, XploRe
Changed by Changed by: Mgr. Jiří Zelinka, Dr., učo 72. Changed: 23/9/2005 14:04.
Abstract
This book offers a detailed application guide to XploRe - the interactive statistical computing environment - with case studies of real data analysis situations. It helps the beginner in statistical data analysis to learn in gradual steps how XploRe works in real life applications. Many examples from practice are discussed and analysed in full length. Great emphasis is put on graphics based understanding of the data interrelations. The case studies include: Survival modelling with Cox's proportional hazard regression.- Vitamine C data analysis with Quantile Regression.- Human capital allocation with smoothing methods.- Cluster analysis of butterfly data.- Money market analysis with Dynamic Partial Least Squares.- Media metrics with correspondance analysis.- Multiple and flexible time series analysis of macro economic data.- As well as other case studies.
Links
MSM 143100001, plan (intention)Name: Funkcionální diferenciální rovnice a matematicko-statistické modely
Investor: Ministry of Education, Youth and Sports of the CR, Functional-differential equations and mathematical-statistical models
PrintDisplayed: 26/7/2024 03:37