Smoothing Spline ANOVA Models.pdf

Smoothing Spline ANOVA Models PDF

Chong Gu

Nonparametric function estimation with stochastic data, otherwise known as smoothing, has been studied by several generations of statisticians. Assisted by the ample computing power in todays servers, desktops, and laptops, smoothing methods have been finding their ways into everyday data analysis by practitioners. While scores of methods have proved successful for univariate smoothing, ones practical in multivariate settings number far less. Smoothing spline ANOVA models are a versatile family of smoothing methods derived through roughness penalties, that are suitable for both univariate and multivariate problems. In this book, the author presents a treatise on penalty smoothing under a unified framework. Methods are developed for (i) regression with Gaussian and non-Gaussian responses as well as with censored lifetime data

Fit smoothing spline ANOVA models in Gaussian regression. The symbolic model specification via formula follows the same rules as in lm . Smoothing Splines - MATLAB & Simulink

1461453690 ISBN
Englisch SPRACHE
Smoothing Spline ANOVA Models.pdf


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Sofia Voigt

Smoothing spline ANOVA models (Book, 2002) … Note: Citations are based on reference standards. However, formatting rules can vary widely between applications and fields of interest or study. The specific requirements or preferences of your reviewing publisher, classroom teacher, institution or organization should be applied.

Matteo Müller

We propose a new method for model selection and model fitting in multivariate nonparametric regression models, in the framework of smoothing spline ANOVA. The “COSSO” is a method of regularization with the penalty functional being the sum of component norms, instead of the squared norm employed in the traditional smoothing spline method P-SPLINE ANOVA-TYPE INTERACTION MODELS FOR SPATIO …

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Smoothing Spline ANOVA for variable screening

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26.01.2013 · Read "Smoothing Spline ANOVA Models" by Chong Gu available from Rakuten Kobo. Nonparametric function estimation with stochastic data, otherwise known as smoothing, has been studied by several genera Bayesian smoothing spline analysis of variance - …

Jessica Kohmann

This is based on an ANOVA-type decomposition and is called the smoothing spline ANOVA (SSANOVA) model. The decomposition of the estimated func- tion into ... Jan 10, 2011 ... We propose the use of penalized splines ( -splines) in a mixed model framework for smoothing spatio-temporal data. Our approach allows the ...