Mixed-Effects REML Incorporating Generalized Inverses
Optimization Algorithm Checks.
anova() for gremlin objects
Convergence Criteria Checks for REML.
Partial sparse matrix inverse from a Cholesky factorization.
(Co)variance parameter transformations.
Delta Method to Calculate Standard Errors for Functions of (Co)varianc...
Fixed Effect Estimates of class gremlin
Mixed-Effects REML Incorporating Generalized Inverses
Mixed-effect modeling functions.
Advanced Options for Mixed-effect modeling functions.
Methods to extract log-likelihood and information criterion of a greml...
Number of observations in data from gremlin model fit objects
REML optimization algorithms for mixed-effect models.
Mixed-effect model Restricted Maximum Likelihood (REML) iterations.
Residuals of class gremlin
Time to execute the gremlin model
Gremlin model summary.
Matrix trace methods.
Fit linear mixed-effects models using restricted (or residual) maximum likelihood (REML) and with generalized inverse matrices to specify covariance structures for random effects. In particular, the package is suited to fit quantitative genetic mixed models, often referred to as 'animal models'. Implements the average information algorithm as the main tool to maximize the restricted log-likelihood, but with other algorithms available.