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impute_nondetect() gains a control
argument accepting a survival::survreg.control() object.
This allows users to tune the underlying survreg fitting
algorithm - most notably maxiter - for datasets where the
default iteration limit causes convergence warnings.impute_nondetect() gains a zero_value
argument (default 1e-5): exact zeros are replaced by it
when fitting the log-normal, Weibull, exponential and log-logistic
distributions, which previously failed silently on data containing
zeros. The zeros are kept in the final values.impute_nondetect() now records the AIC and convergence
of every distribution (attribute fits) and selects the best
model among the converged fits only. If none converged, the best
non-converged fit is used, a warning is raised, and attribute
best_converged is FALSE. Convergence warnings
from the individual fits are no longer passed on to the caller.min_value = 0, logistic imputations were
not truncated at 0, and draws below 0 were set to exactly 0. They are
now drawn from the logistic truncated between min_value and
the detection limit.These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.