Generalized additive modelsThis paper describes a flexible method for modelling zero inflated count data which are typically found when trying to model and predict species distributions. Zero inflated data are defined as data that has a larger proportion of zeros than expected from pure count (...
In this context, we should also mention that a widely used modification of the additive model (2.24) is the generalized additive model (GAM), which is treated extensively in the book by Hastie and Tibshirani (1990) and in the paper by Hastie and Tibshirani (1993). A link function makes ...
We introduce GAMSEL (Generalized Additive Model Selection), a penalized likelihood approach for fitting sparse generalized additive models in high dimension. Our method interpolates between null, linear and additive models by allowing the effect of each variable to be estimated as being either zero, ...
Paper on identifying patterns in economic development using statistical learning complexityeconomic-developmenteconomic-datageneralized-additive-modelsdiversificationeconomic-growth UpdatedJul 6, 2023 Jupyter Notebook Load more… Improve this page Add a description, image, and links to thegeneralized-additive-mo...
Testing for interactions in generalized additive models: Application to SO2 pollution data In this paper we considered a generalized additive model with second-order interaction terms. A local scoring algorithm (with backfitting) based on local l... J Roca-Pardi?As,C Cadarso-Suárez,W González-Ma...
additiveterms,thenmodel(4)isreducedtoanon-linearparametric G A M LSS model. gk(θ k)=η k=hk( Xk,β k). (5) If,inaddition,hk(Xk,β )= X >β fori=1,2,...,nandk=1,2,3,4then(5)reducestothe k k k linearparametricmodel(3). Notethatsomeofthetermsineachhk(Xk,β k...
The purpose of this paper was to introduce the concepts,functions and the calculation methods by using the statistical software of the regression analysis based on the additive model and generalized additive model. Firstly,the basic concepts of the regression analysis were introduced. Secondly,the basi...
Inferring cellular trajectories using a variety of omic data is a critical task in single-cell data science. However, accurate prediction of cell fates, and thereby biologically meaningful discovery, is challenged by the sheer size of single-cell data, t
In this paper, an explainable neural network based on generalized additive models with structured interactions (GAMI-Net) is proposed to pursue a good balance between prediction accuracy and model interpretability. GAMI-Net is a disentangled feedforward network with multiple additive subnetworks; each ...
2.3. Generalized additive models In this paper, we focus on generalized additive models as a specific type of interpretable models. They have been widely used in high-stake domains where model transparency is a pivotal requirement (Barredo Arrieta, Díaz-Rodríguez, Del Ser, Bennetot, Tabik, ...