Add to ORKG24 pages, 1 article*Maximum Likelihood Algorithms for Generalized Linear Mixed Models* (McCulloch, Charles E.) 24 page
The generalized linear mixed model (GLMM) generalizes the standard linear model in three ways: accom...
This paper provides a unified algorithm to explicitly calculate the maximum likelihood estimates of ...
Spatial generalized linear mixed effects models are popular in spatial or spatiotemporal data analys...
of the diploma thesis Title: Computational Methods for Maximum Likelihood Estimation in Generalized ...
Approximates the likelihood of a generalized linear mixed model using Monte Carlo likelihood approxi...
Maximum likelihood estimation of generalized linear mixed models (GLMMs) is difficult due to margina...
The class of generalized linear models is extended to allow for correlated observations, nonlinear m...
Generalized linear mixed model fit by maximum likelihood (laplace approximation) fixed effects (raw ...
Abstract: A mixture model approach is developed that simultaneously estimates the posterior membersh...
9 pages, 1 article*Deriving Generalized Means as Least Squares and Maximum Likelihood Estimates* (Be...
SUMMARY. This paper proposes a modification of the Fisher–Scoring method, an algorithm which is wide...
13 pages, 1 article*Statistical Inference Using Maximum Likelihood Estimation and the Generalized Li...
We intrduce a new algorithm for 1L regularized generalized linear models. The 1L regularization proc...
Abstract. Estimation of generalized linear mixed models (GLMMs) with non-nested random effects struc...
Non-Gaussian spatial data are common in many sciences such as environmental sciences, biology and ep...
The generalized linear mixed model (GLMM) generalizes the standard linear model in three ways: accom...
This paper provides a unified algorithm to explicitly calculate the maximum likelihood estimates of ...
Spatial generalized linear mixed effects models are popular in spatial or spatiotemporal data analys...
of the diploma thesis Title: Computational Methods for Maximum Likelihood Estimation in Generalized ...
Approximates the likelihood of a generalized linear mixed model using Monte Carlo likelihood approxi...
Maximum likelihood estimation of generalized linear mixed models (GLMMs) is difficult due to margina...
The class of generalized linear models is extended to allow for correlated observations, nonlinear m...
Generalized linear mixed model fit by maximum likelihood (laplace approximation) fixed effects (raw ...
Abstract: A mixture model approach is developed that simultaneously estimates the posterior membersh...
9 pages, 1 article*Deriving Generalized Means as Least Squares and Maximum Likelihood Estimates* (Be...
SUMMARY. This paper proposes a modification of the Fisher–Scoring method, an algorithm which is wide...
13 pages, 1 article*Statistical Inference Using Maximum Likelihood Estimation and the Generalized Li...
We intrduce a new algorithm for 1L regularized generalized linear models. The 1L regularization proc...
Abstract. Estimation of generalized linear mixed models (GLMMs) with non-nested random effects struc...
Non-Gaussian spatial data are common in many sciences such as environmental sciences, biology and ep...
The generalized linear mixed model (GLMM) generalizes the standard linear model in three ways: accom...
This paper provides a unified algorithm to explicitly calculate the maximum likelihood estimates of ...
Spatial generalized linear mixed effects models are popular in spatial or spatiotemporal data analys...