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msm (version 1.5)

paramdata.object: Developer documentation: internal msm parameters object

Description

An object giving information about the parameters of the multi-state model. Used internally during maximum likelihood estimation and arranging results. Returned as the paramdata component of a fitted msm model object.

Arguments

Value

  • initsVector of initial values for distinct parameters which are being estimated. These have been transformed to the real line (e.g. by log), and exclude parameters being fixed at their initial values, parameters defined to be always fixed (e.g. binomial denominators) and parameters constrained to equal previous ones.
  • plabsNames of parameters in allinits.
  • allinitsVector of parameter values before estimation, including those which are fixed or constrained to equal other parameters, and transformed to the real line.
  • hmmparsIndices of allinits which represent baseline parameters of hidden Markov outcome models (thus excluding covariate effects in HMMs and initial state occupancy probabilities).
  • fixedTRUE if all parameters are fixed, FALSE otherwise.
  • fixedparsIndices of parameters in allinits which are fixed, either by definition or as requested by the user in the fixedpars argument to msm. Excludes parameters fixed by constraining to equal other parameters.
  • notfixedIndices of parameters which are not fixed by the definition of fixedpars.
  • optparsIndices of parameters in allinits being estimated, thus those included in inits.
  • auxparsIndices of "auxiliary" parameters which are always fixed, for example, binomial denominators (hmmBinom) and the which parameter in hmmIdent.
  • constrVector of integers, of length npars, indicating which sets of parameters are constrained to be equal to each other. If two of these integers are equal the corresponding parameters are equal. A negative element indicates that parameter is defined to be minus some other parameter (this is used for covariate effects on transition intensities).
  • nparsTotal number of parameters, equal to length(allinits).
  • nfixNumber of fixed parameters, equal to length(fixedpars).
  • noptNumber of parameters being estimated, equal to length(inits) and length(optpars).
  • ndupNumber of parameters defined as duplicates of previous parameters by equality constraints (currently unused).
  • rangesMatrix of defined ranges for each parameter on the natural scale (e.g. 0 to infinity for rate parameters).
  • optObject returned by the optimisation routine (such as optim).
  • foundseTRUE if standard errors are available after optimisation. If FALSE the optimisation probably hasn't converged.
  • likMinus twice the log likelihood at the parameter estimates.
  • derivDerivatives of the minus twice log likelihood at the parameter estimates, if available.
  • informationCorresponding expected information matrix at the parameter estimates, if available.
  • paramsVector of parameter values after maximum likelihood estimation, corresponding to allinits, still on the real-line transformed scale.
  • covmatCovariance matrix corresponding to params.
  • ciMatrix of confidence intervals corresponding to params, with nominal coverage (default 0.95) defined by the cl argument of msm.
  • estimates.tVector of parameter estimates, as params but with parameters on their natural scales.

See Also

msm.object