ctsem (version 3.7.2)

ctStanKalman: Get Kalman filter estimates from a ctStanFit object

Description

Get Kalman filter estimates from a ctStanFit object

Usage

ctStanKalman(
  fit,
  nsamples = NA,
  pointest = TRUE,
  collapsefunc = NA,
  cores = 1,
  standardisederrors = FALSE,
  subjectpars = TRUE,
  tformsubjectpars = TRUE,
  indvarstates = FALSE,
  ...
)

Value

list containing Kalman filter elements, each element in array of iterations, data row, variables. llrow is the log likelihood for each row of data.

Arguments

fit

fit object from ctStanFit.

nsamples

either NA (to extract all) or a positive integer from 1 to maximum samples in the fit.

pointest

If TRUE, uses the posterior mode as the single sample.

collapsefunc

function to apply over samples, such as mean

cores

Integer number of cpu cores to use. Only needed if savescores was set to FALSE when fitting.

standardisederrors

If TRUE, computes standardised errors for prior, upd, smooth conditions.

subjectpars

if TRUE, state estimates are not returned, instead, predictions of each subjects parameters are returned, for parameters that had random effects specified.

tformsubjectpars

if FALSE, subject level parameters are returned in raw, pre transformation form.

indvarstates

if TRUE, do not remove indvarying states from output

...

additional arguments to collpsefunc.

Examples

if(w32chk()){
k=ctStanKalman(ctstantestfit,subjectpars=TRUE,collapsefunc=mean)
}