Imports: graphics, grid, splines, MASS, nlme, minqa (>= 1.1.15), Rcpp

Title: Linear Mixed-Effects Models using 'Eigen' and S4
Ben Bolker [aut, cre], Steven Walker [aut],
'Eigen' C++ library for numerical linear algebra and 'RcppEigen' "glue".
Depends: R (>= 3.0.2), Matrix (>= 1.1.1), methods, stats
Imports: graphics, grid, splines, utils, parallel, MASS, nlme, lattice,
Suggests: knitr, boot, PKPDmodels, MEMSS, testthat (>= 0.8.1), ggplot2,
mlmRev, optimx (>= 2013.8.6), gamm4, pbkrtest, HSAUR2, numDeriv

Imports: graphics, grid, splines, utils, parallel, MASS, lattice, nlme

Depends: R (>= 3.2.0), Matrix (>= 1.2-1), methods, stats

mlmRev, optimx (>= 2013.8.6), gamm4, pbkrtest, HSAUR2,
Author: Douglas Bates [aut] (<https://orcid.org/0000-0001-8316-9503>),

Imports: graphics, grid, splines, utils, parallel, MASS, lattice, boot,
Suggests: knitr, rmarkdown, PKPDmodels, MEMSS, testthat (>= 0.8.1),
ggplot2, mlmRev, optimx (>= 2013.8.6), gamm4, pbkrtest, HSAUR2,

person("Pavel N.", "Krivitsky", role=c("ctb","cph"), comment=c(ORCID="0000-0002-9101-3362",
ggplot2, mlmRev, optimx (>= 2013.8.6), gamm4, pbkrtest, HSAUR3,
Pavel N. Krivitsky [ctb, cph] (<https://orcid.org/0000-0002-9101-3362>,

numDeriv, car, dfoptim, mgcv, statmod, rr2, semEff

numDeriv, car, dfoptim, mgcv, statmod, rr2, semEff, tibble

Suggests: knitr, rmarkdown, MEMSS, testthat (>= 0.8.1), ggplot2,
mlmRev, optimx (>= 2013.8.6), gamm4, pbkrtest, HSAUR3,
numDeriv, car, dfoptim, mgcv, statmod, rr2, semEff, tibble,

Depends: R (>= 3.5.0), Matrix (>= 1.2-1), methods, stats

Depends: R (>= 2.14.0), Matrix (>= 1.1.1), methods, stats, Rcpp (>=
Imports: graphics, grid, splines, parallel, MASS, nlme, lattice, minqa

Depends: R (>= 2.15.1), Matrix (>= 1.1.1), methods, stats, Rcpp (>=
Packaged: 2014-04-11 19:12:22 UTC; stevenwalker

mlmRev, optimx (>= 2013.8.6), gamm4, pbkrtest

Title: Information Matrices for 'lmeStruct' and 'glsStruct' Objects
Description: Provides analytic derivatives and information matrices for
fitted linear mixed effects (lme) models and generalized least squares (gls) models
estimated using lme() (from package 'nlme') and gls() (from package 'nlme'), respectively.
The package includes functions for estimating the sampling variance-covariance of variance
component parameters using the inverse Fisher information. The variance components include
the parameters of the random effects structure (for lme models), the variance structure,
and the correlation structure. The expected and average forms of the Fisher information matrix
are used in the calculations, and models estimated by full maximum likelihood or
restricted maximum likelihood are supported. The package also includes a function for estimating
standardized mean difference effect sizes (Pustejovsky, Hedges, and Shadish (2014) <DOI:10.3102/1076998614547577>)
Suggests: covr, testthat (>= 2.1.0), knitr, rmarkdown, scdhlm, dplyr,
Author: James Pustejovsky [aut] (<https://orcid.org/0000-0003-0591-9465>),