Package: DHARMa
Title: Residual Diagnostics for Hierarchical (Multi-Level / Mixed)
        Regression Models
Version: 0.3.0
Date: 2020-04-19
Authors@R: c(person("Florian", "Hartig", email = "florian.hartig@biologie.uni-regensburg.de", role = c("aut", "cre"), comment=c(ORCID="0000-0002-6255-9059")))
Description: The 'DHARMa' package uses a simulation-based approach to create
    readily interpretable scaled (quantile) residuals for fitted (generalized) linear mixed
    models. Currently supported are linear and generalized linear (mixed) models from 'lme4'
    (classes 'lmerMod', 'glmerMod'), 'glmmTMB' and 'spaMM', generalized additive models ('gam' from
    'mgcv'), 'glm' (including 'negbin' from 'MASS', but excluding quasi-distributions) and 'lm' model
    classes. Moreover, externally created simulations, e.g. posterior predictive simulations
    from Bayesian software such as 'JAGS', 'STAN', or 'BUGS' can be processed as well.
    The resulting residuals are standardized to values between 0 and 1 and can be interpreted
    as intuitively as residuals from a linear regression. The package also provides a number of
    plot and test functions for typical model misspecification problems, such as
    over/underdispersion, zero-inflation, and residual spatial and temporal autocorrelation.
Depends: R (>= 3.0.2)
Imports: stats, graphics, utils, grDevices, parallel, doParallel,
        foreach, gap, lmtest, ape, sfsmisc, MASS, lme4, mgcv, glmmTMB
        (>= 1.0.0), spaMM (>= 2.6.0), qgam (>= 1.3.2)
Suggests: knitr, testthat, KernSmooth
License: GPL (>= 3)
URL: http://florianhartig.github.io/DHARMa/
BugReports: https://github.com/florianhartig/DHARMa/issues
LazyData: true
RoxygenNote: 7.0.2.9000
VignetteBuilder: knitr
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2020-04-20 13:14:10 UTC; florian
Author: Florian Hartig [aut, cre] (<https://orcid.org/0000-0002-6255-9059>)
Maintainer: Florian Hartig <florian.hartig@biologie.uni-regensburg.de>
Repository: CRAN
Date/Publication: 2020-04-20 15:30:02 UTC
Built: R 3.5.3; ; 2020-04-22 00:11:30 UTC; windows
