Mixed linear models are used to analyze data in many settings. These models have a multivariate normal formulation in most cases. The maximum likelihood estimator (MLE) or the residual MLE (REML) is ...
This is the true, horrific story of Ed Gein, the 'Butcher of Plainfield' Woman recalls '90s childhood vacations—has sudden realization: "a cover" 65-year-old furloughed by government shutdown: 'I ...
Limitations of linear regression applied on ecological data -- Things are not always linear : additive modeling -- Dealing with heterogeneity -- Mixed effects modeling for nested data -- Violation of ...
Generalized linear mixed models (GLMM) are useful in a variety of applications. With surrogate covariate data, existing methods of inference for GLMM are usually computationally intensive. We propose ...
Keywords: Statistical analyses. Regression models. Post-earthquake ignitions. Data analyses. California. Ground shaking. Generalized linear mixed models. Goodness-of ...
Ordinary linear regression (OLR) assumes that response variables are continuous. Generalized Linear Models (GLMs) provide an extension to OLR since response variables can be continuous or discrete ...
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