Smoothing Spline ANOVA Models

Smoothing Spline ANOVA Models

Nettpris
1 294,-
Førpris 1 849,- Spar 555,-
E-Bok
E-bøkene legges i din ARK-leseapp. Bøkene kan også lastes ned fra Din side.
×
Logg deg inn for å gjennomføre dette kjøpet med ett klikk!

Etter at kjøpet er gjennomført vil boken være tilgjengelig på «din side» og i ARK-appen
Skriv anmeldelse
Format E-Bok
Kopisperre Teknisk DRM
Filformat PDF
Utgivelsesår 2013
Forlag Springer New York
Språk Engelsk
ISBN 9781461453697
Se flere detaljer  

Andre formater / språk

E-Bok Nedlastbar Engelsk
×
Logg deg inn for å gjennomføre dette kjøpet med ett klikk!

Etter at kjøpet er gjennomført vil boken være tilgjengelig på «din side» og i ARK-appen

Om Smoothing Spline ANOVA Models

Nonparametric function estimation with stochastic data, otherwiseknown as smoothing, has been studied by several generations ofstatisticians. Assisted by the ample computing power in today'sservers, desktops, and laptops, smoothing methods have been findingtheir ways into everyday data analysis by practitioners. While scoresof methods have proved successful for univariate smoothing, onespractical in multivariate settings number far less. Smoothing splineANOVA models are a versatile family of smoothing methods derivedthrough roughness penalties, that are suitable for both univariate andmultivariate problems.In this book, the author presents a treatise on penalty smoothingunder a unified framework. Methods are developed for (i) regressionwith Gaussian and non- Gaussian responses as well as with censored lifetime data; (ii) density and conditional density estimation under avariety of sampling schemes; and (iii) hazard rate estimation withcensored life time data and covariates. The unifying themes are thegeneral penalized likelihood method and the construction ofmultivariate models with built-in ANOVA decompositions. Extensivediscussions are devoted to model construction, smoothing parameterselection, computation, and asymptotic convergence.Most of the computational and data analytical tools discussed in thebook are implemented in R, an open-source platform for statisticalcomputing and graphics. Suites of functions are embodied in the Rpackage gss, and are illustrated throughout the book using simulatedand real data examples. This monograph will be useful as a reference work for researchers intheoretical and applied statistics as well as for those in otherrelated disciplines. It can also be used as a text for graduate levelcourses on the subject. Most of the materials are accessible to asecond year graduate student with a good training in calculus andlinear algebra and working knowledge in basic statistical inferencessuch as linear models and maximum likelihood estimates.


Kundevurderinger

ARKs anbefalinger

Det finnes ingen vurderinger av dette produktet. Skriv anmeldelse

Mer fra Chong Gu

Anbefalt


Tips en venn