View source: R/stan_unconstrainsamples.R
stan_unconstrainsamples | R Documentation |
Convert samples from a stanfit object to the unconstrained scale
stan_unconstrainsamples(fit, standata = NA)
fit |
stanfit object. |
standata |
only necessary if R session has been restarted since fitting model – used to reinitialize stanfit object. |
Matrix containing columns of unconstrained parameters for each post-warmup iteration.
#get data
sunspots<-sunspot.year
sunspots<-sunspots[50: (length(sunspots) - (1988-1924))]
id <- 1
time <- 1749:1924
datalong <- cbind(id, time, sunspots)
#setup model
ssmodel <- ctModel(type='stanct', n.latent=2, n.manifest=1,
manifestNames='sunspots',
latentNames=c('ss_level', 'ss_velocity'),
LAMBDA=matrix(c( 1, 'ma1| log(1+(exp(param)))' ), nrow=1, ncol=2),
DRIFT=matrix(c(0, 'a21 | -log(1+exp(param))', 1, 'a22'), nrow=2, ncol=2),
MANIFESTMEANS=matrix(c('m1|param * 10 + 44'), nrow=1, ncol=1),
MANIFESTVAR=diag(0,1), #As per original spec
CINT=matrix(c(0, 0), nrow=2, ncol=1),
DIFFUSION=matrix(c(0, 0, 0, "diffusion"), ncol=2, nrow=2))
#fit
ssfit <- ctStanFit(datalong, ssmodel,
iter=200, chains=2,optimize=FALSE, priors=TRUE,control=list(max_treedepth=4))
umat <- stan_unconstrainsamples(ssfit$stanfit$stanfit)
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