Description: Compute analytic case-wise and cluster-wise derivatives for mixed effects models with respect to fixed effect parameters, random effect (co)variances, and residual variances.
Author: Ting Wang [aut, cre], Edgar Merkle [aut]

Depends: R (>= 3.2.3), lme4 (>= 1.1-10), stats, methods, nonnest2,

Description: Compute case-wise and cluster-wise derivative for

Description: Compute case-wise and cluster-wise derivative for mixed effects models with respect to fixed effects parameter, random effect (co)variances, and residual variance. This material is partially based on work supported by the National Science Foundation under Grant Number 1460719.
Imports: utils, Matrix, matrixcalc, numDeriv

Imports: utils, Matrix, numDeriv, lmeInfo

Title: Tools for Analyzing Mixed Effect Regression Models
Authors@R: c(person(c("Jared", "E."), "Knowles", email = "jknowles@gmail.com",
role = c("aut", "cre")), person("Carl", "Frederick", email="carlbfrederick@gmail.com",
Description: Provides methods for extracting results from merMod objects in the lme4 package. Allows construction of prediction intervals efficiently from large scale LMM and GLMM models.
Depends: R (>= 3.0.2), arm, lme4, methods
Imports: mvtnorm, DT, shiny, plyr, abind, ggplot2

Description: Provides methods for extracting results from mixed-effect model
objects fit with the lme4 package. Allows construction of prediction intervals
efficiently from large scale linear and generalized linear mixed-effects models.
Depends: R (>= 3.0.2), arm, lme4, methods, plyr
Suggests: testthat, knitr, rmarkdown, dplyr, foreach, parallel
Imports: mvtnorm, DT, shiny, abind, ggplot2, blme, broom

objects fit with the 'lme4' package. Allows construction of prediction intervals
Depends: R (>= 3.0.2), arm, lme4 (>= 1.1-11), methods, plyr

Depends: R (>= 3.0.2), arm, lme4 (>= 1.1-11), methods, dplyr
Suggests: testthat, knitr, rmarkdown, foreach, parallel, rstanarm

person(c("Jared", "E."), "Knowles", email = "jknowles@gmail.com", role = c("aut", "cre")),
person("Carl", "Frederick", email="carlbfrederick@gmail.com", role = c("aut")),
person("Alex", "Whitworth", email="whitworth.alex@gmail.com", role = c("ctb")))
Suggests: testthat, knitr, rmarkdown, parallel, rstanarm, Amelia, nlme
Imports: mvtnorm, DT, shiny, abind, ggplot2, blme, broom, foreach