Combines several locations and covariates for several STmodel/STdata objects. Temporal trend, observations and covariance model (both spatial and spatio-temporal) are taken from the first object in the call. Any additional covariates/trends/observations not present in the first argument are dropped from the additional arguments without warning. Locations and covariates (both spatial and spatio-temporal) from additional objects are added to those in the first object.
# S3 method for STmodel
c (..., recursive = FALSE)
STmodel
and STdata
objects to
combine, the first object has to be a STmodel
.
For S3 compatibility; the function will ALWAYS run recursively
An updated STmodel
object.
For additional STdata
objects the covariates are
transformed according to STmodel$scale.covars
of
the first object, see createSTmodel
.
For STmodel
objects can not be combined
if either has scaled covariates.
Other STdata functions: createDataMatrix
,
createSTdata
, createSTmodel
,
detrendSTdata
,
estimateBetaFields
,
removeSTcovarMean
,
updateSTdataTrend
,
updateTrend
,
updateTrend.STdata
,
updateTrend.STmodel
Other STmodel methods: createSTmodel
,
estimate
, estimate.STmodel
,
estimateCV
,
estimateCV.STmodel
, MCMC
,
MCMC.STmodel
, plot.STdata
,
plot.STmodel
,
predict.STmodel
, predictCV
,
predictCV.STmodel
,
print.STmodel
,
print.summary.STmodel
,
qqnorm.predCVSTmodel
,
qqnorm.STdata
,
qqnorm.STmodel
,
scatterPlot.predCVSTmodel
,
scatterPlot.STdata
,
scatterPlot.STmodel
,
simulate.STmodel
,
summary.STmodel
# NOT RUN {
##load the data
data(mesa.data.raw)
##and create STdata-object
mesa.data <- createSTdata(mesa.data.raw$obs, mesa.data.raw$X, n.basis=2,
SpatioTemporal=mesa.data.raw["lax.conc.1500"])
##keep only observations from the AQS sites
ID.AQS <- mesa.data$covars$ID[ mesa.data$covars$type=="AQS" ]
mesa.data$obs <- mesa.data$obs[mesa.data$obs$ID %in% ID.AQS,]
##model specification
LUR <- list(~log10.m.to.a1 + s2000.pop.div.10000 + km.to.coast,
~km.to.coast, ~km.to.coast)
locations <- list(coords=c("x","y"), long.lat=c("long","lat"), others="type")
##create reduced model, without and with a spatio-temporal covariate.
mesa.model <- createSTmodel(mesa.data, LUR=LUR, locations=locations,
strip=TRUE)
mesa.model.ST <- createSTmodel(mesa.data, LUR=LUR, ST=1,
locations=locations, strip=TRUE)
##and non stripped version
mesa.model.full <- createSTmodel(mesa.data, LUR=LUR, ST=1,
locations=locations)
##combine, this adds the missing locations
mesa.model$locations$ID
c(mesa.model, mesa.data)$locations$ID
##or we could study the summary output
print(c(mesa.model.ST, mesa.data))
##no change since we're tryin to adding existing sites
mesa.model.full$locations$ID
c(mesa.model.full, mesa.data)$locations$ID
##We can also combine two STmodels
print(c(mesa.model, mesa.model.full))
# }
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