Fit a Bayesian Latent Factor to a data set using STAN
Fit a Bayesian Latent Factor to a data set using STAN
modelFit( model = "PLT", var.prior = "IG", prog = "stan", parallel = TRUE, Xhisto = NULL, nchains = 4, nthin = 10, niter = 10000, R = NULL )
model |
a string indicating the type of model ("PLT", or sparse", default = "PLT") |
var.prior |
the family of priors to use for the variance parameters ("IG" for inverse gamma, or "cauchy") |
prog |
a string indicating the MCMC program to use (default = "stan") |
parallel |
true or false, whether or not to parelleize (done using the package "parallel") |
Xhisto |
matrix of simulated data (projected onto the histogram basis) |
nchains |
number of chains (default = 2) |
nthin |
the number of thinned interations (default = 1) |
niter |
number of iterations (default = 1e4) |
R |
rotation matrix of the same dimension as the number of desired latent factors |
stanfit, a STAN object
Gabrielle Weinrott
The Stan Development Team Stan Modeling Language User's Guide and Reference Manual. http://mc-stan.org/
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