gam: Generalized Additive Models
gam uses the backfitting algorithm to combine different smoothing or fitting methods. The methods currently supported are local regression and smoothing splines
Generalized Additive Models
procedure we call the local scoring algorithm. The technique is applicable to any likelihood-based regression model: the class of generalized linear models.
Generalized additive model example in R
One task among others in a regression analysis is to find the right transformation on the predictors. Additive models can help here. Let's fit an additive model
Generalized Additive Models: Some Applications
The local scoring algorithm is analogous to the iterative reweighted least squares algorithm for solving likelihood and nonlinear regression equations. At each
gamselBayes: Bayesian generalized additive model selection
The R package gamselBayes implements algorithms for Bayesian generalized additive model selection developed by and described in He & Wand (2022). The
Generalized Additive Model Multiple Imputation by Chained
The R package ImputeRobust described. The R Journal Vol. 10/1
mgcv: Mixed GAM Computation Vehicle with Automatic Smoothness
Jul 11 2023 Description Generalized additive (mixed) models
gamm4: Generalized Additive Mixed Models using mgcv and lme4
Description Estimate generalized additive mixed models via a version of function gamm() from 'mgcv' using 'lme4' for estimation. Depends R (>= 2.9.0)
Generalized Additive Models
procedure we call the local scoring algorithm. The technique is applicable to any likelihood-based regression model: the class of generalized linear models.
378-2008: Fitting Generalized Additive Models with the GAM
Additive models assume nonparametric smoothing splines for predictors in regression models. Generalized linear models assume the dependency of the dependent
A Markov-Switching Generalized Additive Model for Compound
A Markov-Switching Generalized Additive Model for. Compound Poisson Processes with Applications to. Operational Losses Models. J. Hambuckers1
Some Theory for Penalized Spline Generalized Additive Models
24 août 1999 A particularly attractive example of this is through use of penalized splines (Marx and Eilers 1998). Such an approach has a number of ...
gam: Generalized Additive Models
July 4 2022. Type Package. Title Generalized Additive Models. Date 2020-6-27. Version 1.20.2. Author Trevor Hastie. Description Functions for fitting and
Generalized additive model example in R
One task among others in a regression analysis is to find the right transformation on the predictors. Additive models can help here. Let's fit an additive model
Applying Generalized Additive Mixed Modeling: Tuscan Dialects vs
8 juin 2012 generalized additive model (GAM): relationship between individual predictors and (possibly transformed) dependent variable is estimated by a ...
Generalized Additive Models
Given a sample estimates of #3
WORKING PAPER Reconciling Performance and Interpretability in
To build a successful customer churn prediction model a classification algorithm based on Bagging and RSM
Generalized Additive Models: Some Applications
TREVOR HASTIE and ROBERT TIBSHIRANI*. Generalized additive models have the form q(x) = a +. If(xj)
Generalized Additive Models: an introduction with R COPYRIGHT
1.7 General linear model specification in R A Generalized Additive Model (GAM) is a GLM in which part of the linear pre-.
WORKING PAPER Ensemble classification based on generalized
Generalized additive models (GAMs) are a generalization of generalized linear models (GLMs) and constitute a powerful technique which has successfully
