# Developer documentation: internal msm parameters object

Source:`R/internals_doc.R`

`paramdata.object.Rd`

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.

## Value

- inits
Vector 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.

- plabs
Names of parameters in

`allinits`

.- allinits
Vector of parameter values before estimation, including those which are fixed or constrained to equal other parameters, and transformed to the real line.

- hmmpars
Indices of

`allinits`

which represent baseline parameters of hidden Markov outcome models (thus excluding covariate effects in HMMs and initial state occupancy probabilities).- fixed
`TRUE`

if all parameters are fixed,`FALSE`

otherwise.- fixedpars
Indices 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.- notfixed
Indices of parameters which are not fixed by the definition of

`fixedpars`

.- optpars
Indices of parameters in

`allinits`

being estimated, thus those included in`inits`

.- auxpars
Indices of "auxiliary" parameters which are always fixed, for example, binomial denominators (

`hmmBinom`

) and the`which`

parameter in`hmmIdent`

.- constr
Vector 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).- npars
Total number of parameters, equal to

`length(allinits)`

.- nfix
Number of fixed parameters, equal to

`length(fixedpars)`

.- nopt
Number of parameters being estimated, equal to

`length(inits)`

and`length(optpars)`

.- ndup
Number of parameters defined as duplicates of previous parameters by equality constraints (currently unused).

- ranges
Matrix of defined ranges for each parameter on the natural scale (e.g. 0 to infinity for rate parameters).

- opt
Object returned by the optimisation routine (such as

`optim`

).- foundse
`TRUE`

if standard errors are available after optimisation. If`FALSE`

the optimisation probably hasn't converged.- lik
Minus twice the log likelihood at the parameter estimates.

- deriv
Derivatives of the minus twice log likelihood at the parameter estimates, if available.

- information
Corresponding expected information matrix at the parameter estimates, if available.

- params
Vector of parameter values after maximum likelihood estimation, corresponding to

`allinits`

, still on the real-line transformed scale.- covmat
Covariance matrix corresponding to

`params`

.- ci
Matrix of confidence intervals corresponding to

`params`

, with nominal coverage (default 0.95) defined by the`cl`

argument of`msm`

.- estimates.t
Vector of parameter estimates, as

`params`

but with parameters on their natural scales.