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Initial release of the reorganised package.
sim_mspdata() supports irregular, subject-specific
visit schedules, random missed visits, exactly observed absorption
times, and Weibull (semi-Markov) holding times for assessing the Markov
assumption.fit_msm() replaces fit.msm(), whose name
collided with S3 dispatch on objects of class msm.
fit.msm() and sim.mspdata() remain as
deprecated aliases.fit_msm() validates state coding, duplicate visit times
and observed transitions against the assumed structure before calling
the optimiser, supports deathexact for exactly observed
absorption, and reports the optimiser’s convergence code.ms_montecarlo() reports Monte Carlo standard errors
alongside bias, RMSE and coverage, and counts non-convergence from the
optimiser code rather than from the absence of an error.fit_msm() recovers from the numerical overflow that
msm can hit in large samples by refitting with a rescaled
objective, and records this in the rescaled element. The
retry runs only after an unscaled attempt has failed, so ordinary fits
are unchanged.msm.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.
Health stats visible at Monitor.