We propose a two-step estimating procedure for generalized additive partially linear models with clustered data using estimating equations. Our proposed method applies to the case that the number of ...

Interpretability has drawn increasing attention in machine learning. Partially linear additive models provide an attractive middle ground between the simplicity of generalized linear model and the ...

Generalized additive models (GAMs) are commonly used in ecological research for their ability to model complex nonlinear relationships. However, assessing predictor importance in the presence of ...

This is a preview. Log in through your library . Abstract Generalized additive models are a popular class of multivariate non-parametric regression models, due in large part to the ease of use of the ...

Many response variables are handled poorly by regression models when the errors are assumed to be normally distributed. For example, modeling the state damaged/not damaged of cells after treated with ...

In many applications, the response variable is not Normally distributed. GLM can be used to analyze data from various non-Normal distributions. In this short course, we will introduce two most common ...

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In generalized linear models, the response is assumed to possess a probability distribution of the exponential form. That is, the probability density of the response Y for continuous response ...