Imports: methods, TMB (>= 1.7.13), lme4 (>= 1.1-10), Matrix, nlme
bbmle (>= 1.0.19), pscl, MCMCpack, coda, reshape2, plyr
Packaged: 2018-07-02 12:46:33 UTC; molliebrooks

Suggests: knitr, rmarkdown, testthat, MASS, lattice, ggplot2 (>=
2.2.1), mlmRev, bbmle (>= 1.0.19), pscl, coda, reshape2, car,
emmeans, estimability, DHARMa, multcomp, MuMIn, effects,
Packaged: 2019-01-11 15:28:42 UTC; molliebrooks
Author: Arni Magnusson [aut] (<https://orcid.org/0000-0003-2769-6741>),
Mollie Brooks [aut, cre] (<https://orcid.org/0000-0001-6963-8326>)

2.2.1), mlmRev, bbmle (>= 1.0.19), pscl, coda, reshape2, car
(>= 3.0.6), emmeans (>= 1.4), estimability, DHARMa, multcomp,
MuMIn, effects (>= 4.0-1), dotwhisker, broom, broom.mixed,
plyr, png, boot, texreg, xtable, huxtable
Packaged: 2020-02-03 18:18:40 UTC; molliebrooks

person("Joseph", "O'Brien", role = "ctb",
Packaged: 2020-03-15 15:22:09 UTC; molliebrooks

plyr, png, boot, texreg, xtable, huxtable, numDeriv
Packaged: 2020-07-01 16:12:24 UTC; molliebrooks

plyr, png, boot, texreg, xtable, huxtable, mvabund

Packaged: 2022-03-13 15:15:34 UTC; molliebrooks
Author: Mollie Brooks [aut, cre] (<https://orcid.org/0000-0001-6963-8326>),

Packaged: 2022-07-11 10:01:41 UTC; molliebrooks

plyr, png, boot, texreg, xtable, huxtable, mvabund, parallel
Packaged: 2022-11-16 10:26:44 UTC; molliebrooks
Daniel B. Stouffer [ctb] (<https://orcid.org/0000-0001-9436-9674>)

Title: Bootstrap Resampling for Mixed Effects and Plain Models
Authors@R: person("Colman", "Humphrey", email = "humphrc@tcd.ie",
Description: Performs bootstrap resampling for most models that update() works for. There
are two main functions: BootGlmm() performs block resampling if random effects
are present, and case resampling if not; BootCI() converts output from
bootstrap model runs into confidence intervals and p-values. By default,
Package motivated by Humphrey and Swingley (2018) <arXiv:1805.08670>.
Packaged: 2018-05-23 01:55:38 UTC; colmanhumphrey

Packaged: 2018-09-04 02:57:28 UTC; colmanhumphrey

are two primary functions: bootstrap_model() performs block resampling if random effects
are present, and case resampling if not; bootstrap_ci() converts output from
Suggests: glmmTMB (>= 0.2.1), testthat (>= 0.11.0), parallel (>=
3.0.0), future.apply (>= 1.1.0), knitr, rmarkdown, covr
Packaged: 2019-09-02 17:29:38 UTC; colmanhumphrey