abatchModel: A Batch Modeing Training Inner Functions
In sptemExp: Constrained Spatiotemporal Mixed Models for Exposure Estimation

Description Usage Arguments Details Value Examples

This function is for a batch training models. The users can call parSpModel rather than this for training of multiple models.

1	abatchModel(td,bnd,fS,iF,iT,tidF,tids,mPath,idF="siteid",dateF="date",obsF="obs",nM)

`td`	Training dataset
`bnd`	Map object used in spatial effect model. For specific format, refer to BayesX
`fS`	Formular string
`iF`	Staring time id
`iT`	Ending time id
`tidF`	Time field name
`tids`	Time vector
`mPath`	The path for the models trained to be saved
`idF`	location id name
`dateF`	Date or time field name
`obsF`	observed value field name
`nM`	number of models to be trained

This is an inner function to be called by parSpModel.

The trained models will be saved on the appointed path. No direct output for this function.

#An example of PM2.5 data from Shandong

dPath=tempdir()
modelPath=paste(dPath,"/models",sep="")
unlink(modelPath,recursive = TRUE)
dir.create(modelPath)

data("trainsample","bnd")
aform=paste0('logpm25 ~sx(rid,bs ="mrf",map =bnd)+sx(monthAv,bs="rw2")')
aform=paste0(aform,'+sx(ndvi,bs="rw2")+sx(aod,bs="rw2")+sx(wnd_avg,bs="rw2")')

formulaStrs=c(aform)

trainsample$tid=as.numeric(strftime(trainsample$date,format= "%j"))
trainsample$logpm25=log(trainsample$pm25)
tids=c(91)
abatchModel(trainsample,bnd,formulaStrs,1,1,"tid",tids,modelPath,"siteid","date","pm25",3)