EM_multinomial {icmstate} | R Documentation |
Helper function for npmsm()
Description
For a general Markov chain multi-state model with interval censored transitions calculate the NPMLE using an EM algorithm with multinomial approach
Usage
EM_multinomial(
gd,
tmat,
tmat2,
inits,
beta_params,
support_manual,
exact,
maxit,
tol,
conv_crit,
manual,
verbose,
newmet,
include_inf,
checkMLE,
checkMLE_tol,
prob_tol,
remove_bins,
init_int = init_int,
...
)
Arguments
gd |
A
The true transition time between states is then interval censored between the times. |
tmat |
A transition matrix as created by |
inits |
Which distribution should be used to generate the initial estimates
of the intensities in the EM algorithm. One of c("equalprob", "unif", "beta"),
with "equalprob" assigning 1/K to each intensity, with K the number of distinct
observation times ( |
beta_params |
A vector of length 2 specifying the beta distribution parameters
for initial distribution generation. First entry will be used as |
support_manual |
Used for specifying a manual support region for the transitions.
A list of length the number of transitions in |
exact |
Numeric vector indicating to which states transitions are observed at exact times.
Must coincide with the column number in |
maxit |
Maximum number of iterations. |
tol |
Tolerance of the procedure. |
conv_crit |
Convergence criterion. Stops procedure when the difference
in the chosen quantity between two consecutive iterations is smaller
than the tolerance level
Default is "haz". The options "haz" and "lik" can be compared across different
|
manual |
Manually specify starting transition intensities? |
verbose |
Should iteration messages be printed? Default is FALSE |
newmet |
Should contributions after last observation time also be used in the likelihood? Default is FALSE. |
include_inf |
Should an additional bin from the largest observed time to infinity be included in the algorithm? Default is FALSE. |
checkMLE |
Should a check be performed whether the estimate has converged towards a true Maximum Likelihood Estimate? Default is TRUE. |
checkMLE_tol |
Tolerance for checking whether the estimate has converged to MLE. Whenever an estimated transition intensity is smaller than the tolerance, it is assumed to be zero. |
prob_tol |
If an estimated probability is smaller than |
remove_bins |
Should a bin be removed during the algorithm if all
estimated intensities are zero for a single bin? Can improve
computation speed for large data sets. Note that zero means the estimated intensities
are smaller than |
init_int |
A vector of length 2, with the first entry indicating what percentage of mass should be distributed over (second entry) what percentage of all first bins. Default is c(0, 0), in which case the argument is ignored. This argument has no practical uses and only exists for demonstration purposes in the related article. |
... |
Not used yet |
References
Michael G. Hudgens, On Nonparametric Maximum Likelihood Estimation with Interval Censoring and Left Truncation, Journal of the Royal Statistical Society Series B: Statistical Methodology, Volume 67, Issue 4, September 2005, Pages 573-587, doi:10.1111/j.1467-9868.2005.00516.x