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Generalized Additive Models by R.J. Tibshirani, T.J. Hastie

Generalized Additive Models R.J. Tibshirani, T.J. Hastie ebook
Publisher: Chapman and Hall/CRC
ISBN: 0412343908, 9780412343902
Format: pdf
Page: 175

Mar 2, 2014 - Below, I will proceed from a simple linear regression to a generalized additive model to an ordered logistic regression analysis. Apr 10, 2013 - In this study of landslides in Lower Austria, we focus on the model form uncertainty to assess the quality of a flexible statistical modelling technique, the generalized additive model (GAM). Jun 16, 2009 - Generalized additive models are an established tool to model correlations for nonlinear covariates without too much hazzle with the form of the assosiation between predictor and response. (MBI) principle that simultaneously generalizes the maximum entropy and standard least squares principles, and leads to a matrix approximation that is optimal among all generalized additive models in a certain natural parameter space. And I will illustrate the results with nice plots along the way. Aug 14, 2012 - Investigating the influence of synoptic-scale circulation on air quality using self-organizing maps and generalized additive modeling. May 17, 2014 - New book: Beginner's Guide to GAMM with R. Sep 4, 2013 - Partial Spearman's correlation, generalized additive models, and receiver operating characteristic (ROC) analysis were used to assess associations of kynurenines with PLP. Atmospheric Environment, 45, 128-136. Sep 7, 2007 - [註] 本文於2008/01/05 修訂，主要是加強部分內文（紅字部分）的敘述。 原文載點：http://www2.sas.com/proceedings/sugi26/p256-26.pdf. Jun 12, 2011 - Earlier, I looked at the HadCRUT3vgl data set using generalized least squares to investigate whether the trend in temperature since 1995 was statistically significant. It has taken a while but our 'Beginner's Guide to Generalized Additive Mixed Models with R' is finally available as paperback and EBook from www.highstat.com. May 9, 2014 - In previous posts I have looked at how generalized additive models (GAMs) can be used to model non-linear trends in time series data.