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Main functions

call.LLfn2()
Direct call to log-likelihood fuction
.create.block.data.maps()
create data maps and state info for each block
.get.VCE.fromH()
Compute VCE
.initialize.blocks()
create initial block structure
.onegroup.resample.trans.prob()
resamples transition probs for a single group
.Pt()
computes the transition matrix P(t) at a single timepoint given a single vector of covariates and time t
.repackage()
Prepare modelobj data for optimization
.trans.prob.mean()
transition probs using a single mean covariate vector (averaged over all time, all ids) a fixed beta vector
.trans.prob.meanbyt()
mean-by-t transition probs using a fixed beta vector
.trans.prob.sampleavg()
sample-averaged transition probs using a fixed beta vector
.trans.prob.single()
predicted transition probs for a single covariate table and fixed beta vector from t = 1 to t = t.final
empirical.transition.rates()
Compute empirical transition rates in dataset
get.covdata.byid()
Get covariate data by ID
get.data.by.group()
Get covariate data by group
get.event.data()
reassembles the whole panel data by subject
model.fit()
Fit a prepared model
model.setup()
Set up data and model
resample.statistics()
Display summary stats for table of probabilities created by resampling
resample.trans.prob()
Resample transition probabilities
standardize.df0()
Standardize the input dataframe
table.directory()
Display table of directory entries for each transition
table.event.counts()
Display table of event counts
table.model.coeffs()
Display table of coefficients
trans.prob()
Generates predicted transition probabilities
trans2state()
Convert transition probabilities to state probabilities