NOTE: for more news about the package, see
https://github.com/florianhartig/DHARMa/releases
DHARMa 0.5.0
Major changes
For hierarchical models (GLMMs), we changed the default
simulations from the supported model’s default (mostly unconditional) to
conditional simulations (for most of the supported models and packages).
This represents a major change in the calculated scaled residuals and is
implemented to ensure higher power in dispersion and other tests. We
expect different results for calculated residuals using this or older
DHARMa versions. For compatibility, you can use the
argument simulateREs = "user-specified" to change back to
the model’s default (older DHARMa versions). See package
vignette for more details.
In plotResiduals, we increased the threshold for the
automatic change from quantile regression lines to the spline: from
2,000 to 10,000 data points. When it happens, a message is displayed to
warn users. Also, when quantreg = F, the color of the
spline was changed to black because there is no test associated with the
line (as there is for quantile regression).
In plotResiduals, the argument form has
a new functionality. Beyond the syntax data$predictor, it
allows now to use the formula structure ~predictor,
~predictor1+predictor2, ~.,
~predictor|group and
~predictor|group == "group_level" to plot the residuals
against specific/all predictors and grouping variables/levels. This
works for most of the supported model functions. It solves problems with
NAs in datasets that were excluded by the model. #407 / #425
In testCategorical,
recalculateResiduals, testQuantiles,
testSpatialAutocorrelation and
testTemporalAutocorrelation, additional predictors
(catPred, group, sel, predictor,
time, x,y- respectively) can now be specified
as a formula (similar to plotResiduals). This handles rows
with NAs that were excluded by the model automatically.
brms is now supported by DHARMa for simple models,
i.e. models that could also be fit using glmmTMB (no multi-response,
multinomial or structural equation models).
Bugfixes
Fixing error in runBenchmarks.
Fixing inconsistency in testQuantiles() #465. Including
rankTransform() help function.
Minor changes
Using 95% confidence intervals for confidence bands in plots for
testQuantiles(). Before, we were using standard errors (~ 68%
CI).
Vectorize randomization of residuals to improve speed - PR#493
contributed by StaffanBetner.
Adding color legend to testSpatialAutocorrelation().
New function plotResidualsAll() to plot residuals against
multiple predictors/all predictors of the model via
plotResiduals().
New function getPredictorNames() extracts names of fixed and
random effects (predictors) from a model.
testCategorical() now allows additional arguments to boxplot via
…, mainly to allow for appropriate x-axis labels when running
plotResidualsAll().
Improved appearance of user-specified titles via “main” in
plotResiduals().
DHARMa 0.4.7
New Features
Includes support for the package phylolm.
New function for testing residual phylogenetic autocorrelation
testPylogeneticAutocorrelation().
Major change
New optional argument ‘rotation’ in simulateResiduals() for the
rotation of the residual space prior to calculating the quantile
residuals to account for residual covariance as created by temporal,
spatial or phylogenetic autocorrelation.
Minor changes
Residual plots: Option to change the red color for significant
results to any color of preference through options(DHARMaSignalColor =
“red”). This is a good option for color-blind friendly plots.
Documentation: improved help files and vignette.
DHARMa 0.4.6
New Features
new function benchmarkRuntime() for checking runtime of
functions
new function simulatedLRT() to generate a simulated likelihood ratio
test
Bugfixes
fixed issue with parallelization in runBenchmarks
various minor bugfixed and help improvements
DHARMa 0.4.5
Minor changes
included option to simulate mgcv models using the functions
implemented in mgcViz which should improve mgcv compatibility with
DHARMa
Added option to include plot title in plot() #320
Bugfixes
fixed issues with plotting, see #313 and #274
DHARMa 0.4.4
Major changes
remodelled tests so that all tested packages can be used
conditionally
Minor changes
re-introduced glmmTMB to suggests
phyr moved to enhances
re-modelled package unit tests
added RStan, CmdStanR, rjags, BayesianTools to enhances, as they
could be used with DHARMa
moved parallel calculations in runBenchmark to R native parallel
functions
New features
Added rotation option to all functions that create residuals
(simulateResiduals, recalculateResiduals, createDHARMa)
Documentation
Added help comments about autocorrelation structures, in particular
in simulateResiduals, testSpatialAutocorrelation,
testTemporalAutocorrelation
Added example about the use of rotation in
testTemporalAutocorrelation
Improved help of dispersion test
DHARMa 0.4.3
Bugfixes
Removed glmmTMB completely, see #289
DHARMa 0.4.2
Bugfixes
Moved glmmTMB from suggest to import because this package is used in
the vignette, see #289
Minor changes
Added hurricane dataset
Help and vignette updates
phyr added in suggests
DHARMa 0.4.1
Bugfixes
Force method = traditional for refit = T, as it turns out that the
PIT method is not a good idea on the residuals, see #272
DHARMa 0.4.0
This is actually a bugfix release for 0.3.4, but on reflection I
decided that 0.4.0 should have been a minor release, so I pushed the
version number up to 0.4.0
Bugfixes
bugfix in getResiduals, which had consequences for quantile residual
calculations with refit = T
DHARMa 0.3.4
0.3.4 is a relatively important release with various minor
improvements a smaller new features, most noteworthy the support of
glmmAdaptive
New features
added parametric dispersion test in testDispersion (0.3.3.2)
support for glmmAdaptive (0.3.3.1)
new plot for categorical predictors
new plots for result of runBenchmarks
Major changes
Minor changes
changed test statistics in standard dispersion test to standardized
variance, to be more in line with standard dispersion parameters
defaults for plot function unified
removed option to provide no x,y / time in the correlation
tests
recalculateResiduals now allows subsetting #246
better input checking in correlation tests #190
Bugfixes
bugfix in runBenchmarks included in
https://github.com/florianhartig/DHARMa/pull/247
bugfix in testQuantiles
https://github.com/florianhartig/DHARMa/pull/261
bugfix in getRandomState
https://github.com/florianhartig/DHARMa/issues/254
DHARMa 0.3.3
Bugfixes
bugfix in testOutliers, see
https://github.com/florianhartig/DHARMa/issues/197
bugfix in the ecdf / PIT residual function, see
https://github.com/florianhartig/DHARMa/issues/195
DHARMa 0.3.2
Bugfixes
bugfix in testOutliers, see
https://github.com/florianhartig/DHARMa/issues/182
DHARMa 0.3.1
Major changes
added PIT quantile calculations based on suggestion in #168. For
details see ?getQuantiles
Bugfixes
bugfix for passing on parameters to plot.default through
plotR.DHARMa and plotResiduals
Minor changes
added checks / warnings for models fit with weights
DHARMa 0.3.0
New features
quantile regressions switched to qgam, which also calculates
p-values on the quantile estimates
new testQuantiles function, based on the qgam quantile
regressions
Changes
syntax change for plotResiduals, see ?plotResiduals
transformQuantiles is deprecated, functionality included in
residuals()
nearly all functions can now also be called directly with a fitted
model (for computational efficiency, however, it is still recommended to
calculate the residuals first)
qqPlot now shows disribution, dispersion and outlier test
Bugfixes
bugfix #158 for fitting glmmTMB binomial with proportions
DHARMa 0.2.7
New features
added smooth scatter in plotResiduals
https://github.com/florianhartig/DHARMa/commit/da01d8c7a9a74558817e4a73fe826084164cf05d
glmmTMB now fully supported through new compulsory version 1.0 of
glmmTMB, which includes the re.form argument in the simulations required
by DHARMa https://github.com/florianhartig/DHARMa/pull/140
DHARMa 0.2.6
Bugfixes
return of plotResiduals set to invisible
DHARMa 0.2.5
New features
transformQuantiles function added to transform uniform DHARMa
residuals to normal or other residuals
changed plot function names in
https://github.com/florianhartig/DHARMa/releases/tag/v0.1.6.1
Bugfixes
fixed bug with zeroinflation test for k/n binomial data
https://github.com/florianhartig/DHARMa/issues/55
fixed bug with p-value calculation via ecdf
https://github.com/florianhartig/DHARMa/issues/55
DHARMa 0.1.6
New features
option to apply rank tranformation of x values in plotResiduals, see
https://github.com/florianhartig/DHARMa/issues/44
option to convert predictor to factor
random seed is fixed, random state is recorded
Minor changes
changed syntax in tests for sptial / temporal autocorrlation * null
provides now random. Also, custom distance matrices can be provided to
testSpatialAutocorrelation
slight changes to plot layout
Bugfixes
error catching for crashes in plot function
https://github.com/florianhartig/DHARMa/issues/42
bugfix for glmer.nb parametricOverdispersinTest
https://github.com/florianhartig/DHARMa/issues/47
DHARMa 0.1.5
Minor changes
fixes a bug in version 0.1.4 that occurred when running
simulateResiduals with refit = T. Apologies for any inconvenience.
DHARMa 0.1.4
Major changes
new experimental non-parametric dispersion test on simulated
residuals. Extended simulations to compare dispersion tests
Minor changes
supports for binomial with response coded as factor
error catching for refit procedure
https://github.com/florianhartig/DHARMa/issues/18
warnings in case the refit procedure fails or produces identical
parameter values https://github.com/florianhartig/DHARMa/issues/20
DHARMa 0.1.3
Major changes
includes support for model class ‘gam’ from package ‘mgcv’. Required
overwriting the ‘fitted’ function for gam, see
https://github.com/florianhartig/DHARMa/issues/12
Minor changes
plotResiduals includes support for factors
updates to the help
DHARMa 0.1.2
This bugfix release fixes an issue with backwards compatibility
introduced in the 0.1.1 release, which used the ‘startsWith’ function
that is only available in R base since 3.3.0. In 0.1.2, all occurences
of ‘startsWith’ were replaced with ‘grepl’, which restores the
compatibility with older R versions.
DHARMa 0.1.1
including now the negative binomial models from MASS and lme4, as
well as the possibility to create synthetic data from the negative
binomial family
includes a createDHARMa function that allows using the plot
functions of DHARMa also with externally created simualtions, for
example for Bayesian predictive simulations