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Changelog

Source: NEWS.md

nlmixr2extra (development version)

Bug fixes

  • preconditionFit() accepts a decorated covariance method. nlmixr2est reports the sandwich as "|r|,|s|" when a matrix needed the absolute-value correction (or "r+,s+" when it was nudged positive-definite), but the retry loop compared against the bare "r,s", so a good result read as a failure. It then re-preconditioned the already-preconditioned fit until the R matrix was numerically singular and solve() gave up with “system is computationally singular”. A singular preconditioning matrix is now also reported as a preconditioning failure naming the try, rather than as a bare solve() error (#128).

    The same applies to the " (full)" scope suffix nlmixr2est appends when the installed covariance spans theta + residual sigma + Omega rather than the structural-theta block alone (foceiControl(covFull=), TRUE by default), so "r,s (full)" is recognised as the sandwich too. The shape does not matter to preconditionFit(): the preconditioner is widened to whatever parameter space the returned covariance spans.

  • preconditionFit() works again. It built the reparameterized model lines through symengine, which cannot parse an identifier containing a ., so a conventional residual name like add.sd (as nlmixr2Pre_add.sd) raised “SymEngine exception: Parse error” and made the function unusable for most models. The lines are now assembled directly from the preconditioning matrix, which also drops the symengine dependency from this path (#124).

  • preconditionFit() no longer fails with “non-conformable arguments” on a model with random effects. fit$R spans only the population parameters while the fit covariance also carries the omega elements, so the preconditioner is now widened to the covariance’s own parameter space – identity off the theta block – which keeps the theta/omega cross-covariances correct.

New features

  • New multistart() re-estimates a model from many perturbed starting points, so a fit that settled in a local optimum can be recognised. It takes either a fit or a model plus data, works with any estimation method, and returns a nlmixr2Multistart object holding every start’s objective function and parameter estimates alongside the best fit.

    plot() on the result gives the objective-function waterfall (type = "waterfall", the default) and the parameter-stability plot (type = "parameters").

    Starting points are drawn around the initial estimates by "uniform" (the default), "lhs" (Latin hypercube) or "normal" sampling, respecting fixed parameters and declared bounds. By default the candidates are pre-screened with a cheap empirical-Bayes objective evaluation so that only the most promising ones are fully estimated, and each start is cached to disk so that an interrupted run resumes where it left off. See multistartControl() for the options. ## Bug fixes

  • linearize() works on a model with a correlated eta block. The generated model was built by pasting each entry of ui$eta into a model line, but for a correlated block that property also carries the off-diagonal entry – e.g. (eta.cl,eta.v) – which produced mu_(eta.cl,eta.v) = ... and failed to parse. The eta names are now taken from the diagonal of the ini data frame (#126).

  • Regenerate the stored theoFitOde fit. It was built against an older ‘nlmixr2est’, and its saved $control no longer matched what the current estimator expects, so anything that re-ran the model through that control – bootstrapFit(), profile(), or a plain nlmixr2(fit$finalUiEnv, ..., control = fit$control) – failed with “attempt access index 130/129 in VECTOR_ELT”.

nlmixr2extra 5.2.0

CRAN release: 2026-08-04

Bug fixes

  • addorremoveCovariate() no longer turns the iniDf neta1/neta2 columns into character (#110). The row it adds set them to NA_character_, and rbind() promotes the whole column to match, so max() and order() on those columns became lexicographic further downstream – with ten or more etas max() returned "9" rather than 10, so the next eta index collided with an existing one.

  • Ini rows that are built by hand (adding a covariate in addorremoveCovariate(), adding thetas during linearization) no longer hard-code their column list, so they still rbind() with an iniDf that carries the prior column newer versions of lotri add for prior distributions (#109). Both shapes of the data frame are handled, so this works with lotri versions that have the column and versions that do not.

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

CRAN release: 2026-06-07

  • Add focei/foce linearization

  • Add formula interface

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

nlmixr2extra 5.0.0

CRAN release: 2025-11-29

  • 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

CRAN release: 2025-02-17

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

nlmixr2extra 3.0.1

CRAN release: 2024-10-29

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

nlmixr2extra 3.0.0

CRAN release: 2024-09-18

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

nlmixr2extra 2.0.10

CRAN release: 2024-05-29

nlmixr2extra 2.0.9

CRAN release: 2024-01-31

  • 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

CRAN release: 2022-10-22

  • 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

CRAN release: 2022-10-19

  • 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.