Sharing a fit without the original data

Omitting the data when you save

saveFit() takes a data argument. With data = FALSE, the original dataset is left out of the zip:

library(nlmixr2save)

saveFit(fit, data = FALSE) # writes fit.zip with no origData inside

To make that the default for a whole script or report, set the option:

options(nlmixr2save.data = FALSE)

The saved fit is otherwise complete: it still contains the model, the parameter estimates, and (for a standard fit) the prediction/residual columns. Only the input dataset is gone.

Sharing an existing saved fit: nlmixr2saveShare()

If you already have fit.zip (with data), you do not need to re-run anything. nlmixr2saveShare() reads it and writes a stripped sibling zip, leaving the original untouched:

# fit.zip  ->  fit-noData.zip  (data removed, predictions/tables kept)
nlmixr2saveShare("fit")

# fit.zip  ->  fit-noData-noFit.zip  (data AND output tables removed)
nlmixr2saveShare("fit", noFit = TRUE)

nlmixr2saveShare() also accepts a live fit object (it takes the output name from the object), so you can share straight from a session:

nlmixr2saveShare(fit)              # -> fit-noData.zip
nlmixr2saveShare(fit, noFit = TRUE) # -> fit-noData-noFit.zip

It resolves file names through the same nlmixr2save.dir and nlmixr2save.prefix options as the := cache, so it finds prefixed caches in the cache directory and writes the shareable copies alongside them:

options(nlmixr2save.dir = "cache", nlmixr2save.prefix = "mp-")
nlmixr2saveShare("fit") # reads cache/mp-fit.zip -> writes cache/mp-fit-noData.zip

Side effects – what a stripped fit can no longer do

Removing data is not free. The stripped fit still loads, prints, and reports its parameter estimates, but anything that needs what you removed will not work.

Without the original data (-noData, or saveFit(data = FALSE)):

• fit$origData is absent.
• Operations that need the raw dataset fail or are degraded: visual predictive checks (vpcSim() / tidyvpc), re-deriving residuals or predictions (augPred(), addCwres(), addNpde(), …), and re-fitting or updating the model.
• The prediction/residual columns already computed in the fit (IPRED, PRED, CWRES, …) and the parameter tables are unaffected, so printing and standard goodness-of-fit columns still work.

Without the output tables (-noData-noFit, noFit = TRUE):

• The fit loads as a nlmixr2FitCore (an environment), not a nlmixr2FitData data frame – there is no per-observation table, so as.data.frame(fit) has no rows and plots/diagnostics that need those rows will not work.
• The model, parameter estimates (parFixed / parFixedDf), objective (objDf), covariance (omega), eta table (etaObf), and parameter history (parHistData) remain – enough to inspect and report the fitted model.
• This form has no original data either (it is a superset of -noData).

Note on the cache operator

The data option affects saveFit() and nlmixr2saveShare() only. The := caching operator is intentionally left unchanged: it re-attaches the data from the live call on restore, so its cache continues to behave as before.