Description Usage Arguments Details Value Author(s) See Also Examples
Simulate one realisation from a continuoustime Markov process up to a given time.
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qmatrix 
The transition intensity matrix of the
Markov process. The diagonal of

maxtime 
Maximum time for the simulated process. 
covs 
Matrix of timedependent covariates, with one row for each observation time and one column for each covariate. 
beta 
Matrix of linear covariate effects on log transition intensities. The rows correspond to different covariates, and the columns to the transition intensities. The intensities are ordered by reading across rows of the intensity matrix, starting with the first, counting the positive offdiagonal elements of the matrix. 
obstimes 
Vector of times at which the covariates are observed. 
start 
Starting state of the process. Defaults to 1. 
mintime 
Starting time of the process. Defaults to 0. 
The effect of timedependent covariates on the transition intensity matrix for an individual is determined by assuming that the covariate is a step function which remains constant in between the individual's observation times.
A list with components,
states 
Simulated states through which the process moves. This
ends with either an absorption before 
times 
Exact times at which the process changes to the corresponding states 
qmatrix 
The given transition intensity matrix 
C. H. Jackson [email protected]
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