## File: gmEM.Rd

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r-cran-ctmcd 1.4.1-2
 12345678910111213141516171819202122232425262728293031323334353637383940414243444546474849505152535455565758596061 \name{gmEM} \alias{gmEM} \title{ Expectation-Maximization Algorithm } \description{ Function for deriving a Markov generator matrix estimate by an instance of the expectation-maximization algorithm (described by Bladt and Soerensen, 2005) } \usage{ gmEM(tmabs, te, gmguess, eps = 1e-06, niter = 10000, expmethod = "PadeRBS", verbose = FALSE) } \arguments{ \item{tmabs}{ matrix of absolute transition frequencies } \item{te}{ time elapsed in transition process } \item{gmguess}{ initial guess (for generator matrix) } \item{eps}{ stop criterion: stop, if relative change in log-likelihood is smaller than eps } \item{niter}{ stop criterion: maximum number of iterations } \item{expmethod}{ method for computation of matrix exponential, by default "PadeRBS" is chosen (see \code{?expm} from \code{expm} package for more information) } \item{verbose}{ verbose mode } } \details{ A maximum likelihood generator matrix estimate is derived by an instance of the expectation-maximization algorithm. } \references{ M. Bladt and M. Soerensen: Statistical Inference for Discretely Observed Markov Jump Processes. Journal of the Royal Statistical Society B 67(3):395-410, 2005 } \author{ Marius Pfeuffer } \examples{ data(tm_abs) ## Initial guess for generator matrix (absorbing default state) gm0=matrix(1,8,8) diag(gm0)=0 diag(gm0)=-rowSums(gm0) gm0[8,]=0 ## Derive expectation-maximization algorithm generator matrix estimate gmem=gmEM(tmabs=tm_abs,1,gmguess=gm0,verbose=TRUE) gmem }