Fit and summarise a list of ctsem models
Fit and summarise a list of ctsem models
ctFitMultiModel( mlist, datalong, type = "stanct", cores = 2, summaryOutput = TRUE, saveFits = TRUE, summaryArgs = list(), ... )
mlist |
Named list of models |
datalong |
ctsem long format data |
type |
'stanct' for continuous time or 'standt' for discrete time |
cores |
number of cpu cores to use |
summaryOutput |
Generate summary output into ctSummary folder? Large datasets can take some time. |
saveFits |
Save fit objects to working directory? |
summaryArgs |
Additional arguments for ctSummarise. |
... |
Additional arguments for ctStanFit. |
List containing a named list of model fits ($fits), and a compare object ($compare)
## Not run:
if(w32chk()){
sunspots<-data.frame(id=1,
time=do.call(seq,(lapply(attributes(sunspot.year)$tsp,function(x) x))),
sunspots=sunspot.year)
ssmodel1 <- ctModel(type='omx', manifestNames='sunspots', Tpoints=3,
latentNames=c('ss_level', 'ss_velocity'),
LAMBDA=matrix(c( 1, 'ma1| log(1+(exp(param)))' ), nrow=1, ncol=2),
DRIFT=matrix(c(0, 'a21 | -log(1+exp(param))', 1, 'a22'), nrow=2, ncol=2),
MANIFESTMEANS=matrix(c('m1|param * 10 + 44'), nrow=1, ncol=1),
MANIFESTVAR=diag(0,1), #As per original spec
CINT=matrix(c(0, 0), nrow=2, ncol=1),
DIFFUSION=matrix(c(0, 0, 0, "diffusion"), ncol=2, nrow=2))
ssmodel2 <- ssmodel1
ssmodel2$LAMBDA[2] <- 0
fits<-ctFitMultiModel(list(m1=ssmodel1,m2=ssmodel2),datalong = sunspots,
summaryOutput = FALSE,saveFits = FALSE,cores=1)
print(fits$compare)
}
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