Using fit!(glmm(...), nAGQ = 0) provides a faster optimization algorithm at the expense of some small loss of accuracy. For models with a large number of fixed-effects parameters relative to the number of covariance parameters there can be considerable speedup because nAGQ=0 profiles out the fixed-effects parameters as part of the PIRLS iterations, thereby reducing the dimension of the constrained, nonlinear optimization problem passed to an NLopt optimizer
extend OptSummary to include more information and to convey settings for the algorithm add show meth...
Comput Methods Programs Biomed. Author manuscript; available in PMC 2012 Jun 7GGOPT is a derivative-...
The maximum likelihood method is usually chosen to estimate the regression parameters of Generalized...
Deprecate lmm and glmm constructor functions in favor of explicit LinearMixedModel and GeneralizedLi...
This is an R packge to fit (generalized) linear models to large data sets. For data loaded in R memo...
Fit binomial-response GLMs using either a modified-score approach to bias reduction or maximum penal...
The time complexity of each algorithm is approximate, assuming a model with only a single marker eff...
add and document adaptive Gauss-Hermite quadrature for evaluating the deviance of a GLMM add Compat ...
General Better support for multivariate-response-models from brms. Support for cumulative-link-m...
Add a method for αβAc_mul_B! needed when evaluating ranef on a model with nested, vector-valued rand...
Count data can be analyzed using generalized linear mixed models when observations are correlated in...
International audienceWe propose a new fast algorithm to estimate any sparse generalized linear mode...
Use BlockArrays types for the A and L members of LinearMixedModel Create ScalarFactorReTerm and Vect...
To solve an unconstrained nonlinear minimization problem, we propose an optimal algorithm (OA) as we...
This thesis demonstrated how the Newton and BFGS algorithm could be used to solve the standard VGM r...
extend OptSummary to include more information and to convey settings for the algorithm add show meth...
Comput Methods Programs Biomed. Author manuscript; available in PMC 2012 Jun 7GGOPT is a derivative-...
The maximum likelihood method is usually chosen to estimate the regression parameters of Generalized...
Deprecate lmm and glmm constructor functions in favor of explicit LinearMixedModel and GeneralizedLi...
This is an R packge to fit (generalized) linear models to large data sets. For data loaded in R memo...
Fit binomial-response GLMs using either a modified-score approach to bias reduction or maximum penal...
The time complexity of each algorithm is approximate, assuming a model with only a single marker eff...
add and document adaptive Gauss-Hermite quadrature for evaluating the deviance of a GLMM add Compat ...
General Better support for multivariate-response-models from brms. Support for cumulative-link-m...
Add a method for αβAc_mul_B! needed when evaluating ranef on a model with nested, vector-valued rand...
Count data can be analyzed using generalized linear mixed models when observations are correlated in...
International audienceWe propose a new fast algorithm to estimate any sparse generalized linear mode...
Use BlockArrays types for the A and L members of LinearMixedModel Create ScalarFactorReTerm and Vect...
To solve an unconstrained nonlinear minimization problem, we propose an optimal algorithm (OA) as we...
This thesis demonstrated how the Newton and BFGS algorithm could be used to solve the standard VGM r...
extend OptSummary to include more information and to convey settings for the algorithm add show meth...
Comput Methods Programs Biomed. Author manuscript; available in PMC 2012 Jun 7GGOPT is a derivative-...
The maximum likelihood method is usually chosen to estimate the regression parameters of Generalized...