#' Fit new LV model
#'
#' @author Christopher J. Brown
#' @rdname fit_lvmod
#' @export
fit_lvmod <- function(lv_input, dmetric, num.lv = 2,
nburnin = 5000, niter = 100000, nthin = 10){
load.module("glm")
setwd('~/Code/BenthicLatent')
#mindist model
jags <- jags.model('bug/lv_multinom_dists.bug',
data = list('n' = lv_input$N,
'p' = lv_input$p,
'num.lv' = 2,
'd' = dmetric,
'y' = lv_input$y,
'flow' = lv_input$flow),
n.chains = 1)
#Burn in
update(jags, nburnin)
#Extract samples
niter <- niter
nthin <- nthin
nsamp <- round(niter/nthin)
lvmod_out <- coda.samples(jags, variable.names=c("alpha","alphaf","lvs","int", "all.params"), n.iter=niter, thin = nthin)
return(lvmod_out)
}
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