hglmm-internal {hglmm} | R Documentation |
Internal hglmm functions.
breaker(y, K) derivp(npar, K, rho = NULL, expo = FALSE) derivpi(ispd, tpm, npar, dp) est.tpm(states, K, mixture = FALSE) fix.rho(tpm) fix.tpm(x, K, expo) get.gl(theta, K, X, y, cf) get.hgl(theta, K, X, y, cf) get.l(theta, K, X, y, cf) hglmm.em(formula, data, K, theta, expo = TRUE, mixture = FALSE, itmax = 200, crit = "CLL", tolerance = NULL, overpar=FALSE, digits = NULL, verbose = FALSE) hglmm.bf(formula,data,K,theta,mixture=FALSE,itmax=200, tolerance=NULL,overpar=FALSE,digits=NULL,verbose=FALSE) hglmm.lm(formula, data, K, theta, lmc = 10, mixture = FALSE, itmax = 200, crit, tolerance = NULL, overpar=FALSE, digits = NULL, verbose = FALSE) hglmm.nl(formula, data, K, theta, mixture = FALSE, itmax = 200, tolerance = NULL, overpar=FALSE, use.anal=FALSE, ca=FALSE, verbose = FALSE) init.all(formula, data, K = NULL, par0 = NULL, mixture = FALSE, breaks = NULL,expo = FALSE) lmstep(theta, K, X, y, cf, lmc) newstep(theta, K, X, y, cf) recurse(fy, tpm, cf, epsilon, mixture = FALSE) revise.ispd(tpm) revise.model(formula,data,overpar=FALSE) revise.tpm(xi, mixture) sim.mlt(formula, data, ispd, tpm, phi, miss.frac = 0) sim.sngl(blp, ispd, tpm, mf) steepest(K, X, y, cf, theta)
These functions are auxilliary and are not intended to be called by the user.