nlmixr2extra 5.2.0

New features

• New reporting helpers for comparing candidate models: getMinAICFit() returns the fit with the lowest AIC, listModelsTested() builds a Description/AIC/dAIC table ready for pander::pander(), and isBoundaryFit() reports whether a fit has a parameter at its boundary. By default both selection helpers exclude boundary fits. See the new “reporting helpers” article.

Bug fixes

• Fix bootstrapFit(stratVar=), which did not actually resample. The stratified branch called sample(list(uids), ...), and since list(uids) has length one every draw returned the whole vector of subject ids, so the bootstrap datasets did not depend on the seed (#99). Three further problems in the same code are fixed with it: the new subject ids restarted at 1 in each stratum, so subjects from different strata were merged under a shared id; the sample was split across strata by the number of observations rather than the number of subjects, over-weighting strata whose subjects have more records; and rounding each stratum up could return more subjects than nSampIndiv asked for.

• A stratified bootstrap now always draws whole subjects. When stratVar changed within a subject, that subject’s records were split between strata and resampled as separate (partial) subjects; each subject is now stratified by its first value, with a warning.

• nlmixr2extra:::sampling() now resolves its uid_colname default before using it. Called without one it sampled ncol(data) subjects instead of the number of subjects in the data. It also accepts a tibble, which previously produced a one column tibble where a vector of subject ids was expected.

• Fix covarSearchAuto() crashing with “wrong arguments for subsetting an environment” when a covariate is selected; the best model is now re-fit to recover its fit object. Also corrected the forward inclusion test, which had an inverted sign so improving covariates were never selected (#103)

• bootstrapFit() now works for models with a single estimated population parameter, a single random effect, or no random effects at all. Previously the bootstrap summary collapsed 1-row / 1x1 quantile arrays to vectors (and could not summarize a NULL omega), causing bootstrapFit() to error with dim(X) must have a positive length, incorrect number of dimensions, or 'data' must be of a vector type, was 'NULL'. Printing the bootstrap summary of a model with no random effects no longer errors either.

• optimUnisampling() now keeps N and floorT when it retries internally. Before, the recursive call reset them to the defaults, so asking for a sample size other than 1000, or for un-floored values, could silently return 1000 integer samples instead (#97)

• The bundled theoFitOde fit was regenerated and can now be read without the qs2 package. Its origData and parHistData had been serialized with qs2, so without that package installed those slots could not be decoded and fit$dataMergeInner() – and anything built on it, such as the nlmixr2rpt figures – failed.

nlmixr2extra 5.1.0

• Add focei/foce linearization

• Add formula interface

• Add vignettes on linearization, formula interface, log-likelihood profiling and preconditioning.

nlmixr2extra 5.0.0

• Update internal fit to be nlmixr2est 5.0.0 fit object

nlmixr2extra 3.0.3

• Allow raw fits to be returned (or only the parameters)

nlmixr2extra 3.0.2

• Make sure bootstrapped thetas are named. Fixed issue #76

nlmixr2extra 3.0.1

• Remove non-functioning SCM for now (#71)

nlmixr2extra 3.0.0

• New profile() method for likelihood profiling (Issue #1)

nlmixr2extra 2.0.10

• bootstrapFit() fixes se option (Issue #66)

nlmixr2extra 2.0.9

• bootstrapFit() now will be more careful handling NA values so they do not completely affect results (Issue #59)

• bootstrapFit() will now only take the correlation of the non-zero diagonals (Issue #59).

• New method for knit_print() will generate model equations for LaTeX reporting automatically.

• Tests are now skipped if they contain linear compartment models that need gradients when the gradients are not compiled (as in the case of intel c++).

nlmixr2extra 2.0.8

• Use assignInMyNamespace() instead of using the global assignment operator for the horseshoe prior

• Be specific in version requirements (as requested by CRAN checks)

• Move the theoFitOde.rda data build to devtools::document() to reduce CRAN build time (could add more standard models like warfarin for package developers which takes way too much time for CRAN)

nlmixr2extra 2.0.7

• Fix cli issues with the new cli 3.4+ release that will allow bootstrapping to run again (before cli would error, this fixes the donttest issues on CRAN).

• Fixed step-wise covariate selection to work a bit better with the updated UI, thanks to Vishal Sarsani

• Added lasso covariate selection (thanks to Vishal Sarsani)

• Added horseshoe prior covarite selecion (thanks to Vishal Sarsani)

• Added a NEWS.md file to track changes to the package.