M. Tamminga, C. Ahern, and A. Ecay, "Generalized additive mixed models for intraspeaker variation," Linguistics Vanguard, vol. 2, no. s1, 2016.Tamminga, Meredith, Christopher Ahern & Aaron Ecay. 2016. Generalized additive mixed models for intraspeaker variation. Linguistics Vanguard 2(s1). ...
Generalizedadditivemixedmodels Generalized Additive Mixed Models Initial data-exploratory analysis using scatter plots indicated a non linear dependence of the response on predictor variables. To overcome these difficulties, Hastie and Tibshirani (1990) proposed generalized additive models (GAMs). GAMs are ...
Generalized Additive Models:广义加性模型 热度: GeneralizedAdditiveMixedModels Initialdata-exploratoryanalysisusingscatterplotsindicatedanonlineardependenceof theresponseonpredictorvariables.Toovercomethesedifficulties,HastieandTibshirani(1990) proposedgeneralizedadditivemodels(GAMs).GAMsareextensionsofgeneralizedlinear ...
data-science machine-learning statistics regression statistical-models generalized-additive-models Updated Aug 5, 2024 Julia LCBC-UiO / galamm Star 27 Code Issues Pull requests An R package for estimating generalized additive mixed models with latent variables latent-variable-models hierarchical-mode...
Generalized additive mixed models (GAMMs) [8] extend generalized linear mixed models (GLMMs) [12] to allow nonlinear functional forms between independent variables and the response. They provide a flexible modeling framework to use additive nonparametric functions to model the effects of continuous cova...
This paper considers generalized additive mixed models in which the smooth terms are represented using any relatively low rank basis with an associated quadratic penalty imposing smoothness, and estimation is via likelihood, REML or PQL maximization. The paper shows three things. Firstly, how a smooth...
In this paper, we model river discharge data from the Black VoltaRiver, using Generalised Additive Mixed Models (GAMMs) with a space-timeinteraction represented via a tensor product of continuous time and discretespace. River discharge data from January 2000 to December 2009 for the fourgauge ...
Generalized additive mixed models (GAMMs) extend generalized linear mixed models (GLMMs) to allow the covariates to be nonparametrically associated with the response. Estimation of such models for correlated binary data is challenging and estimation techniques often yield contrasting results. Via ...
In this paper, we model river discharge data from the Black Volta River, using Generalised Additive Mixed Models (GAMMs) with a space-time interaction represented via a tensor product of continuous time and discrete space. River discharge data from January 2000 to December 2009 for the four ...
Generalized additive mixed models (GAMMs) extend generalized linear mixed models (GLMMs) to allow the covariates to be nonparametrically associated with the response. Estimation of such models for correlated binary data is challenging and estimation techniques often yield contrasting results. Via ...