c.STmodel {SpatioTemporal} | R Documentation

## Combine Several STmodel/STdata Objects

### Description

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.

### Usage

    ## S3 method for class 'STmodel'
    c(..., recursive = FALSE)

### Arguments

`...` | `STmodel` and `STdata` objects to combine, the first object has to be a `STmodel`.
`recursive` | For S3 compatibility; the function will ALWAYS run recursively

### Details

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.

### Value

An updated `STmodel` object.

### Author(s)

Johan Lindstrom

### See Also

Other STmodel methods: `MCMC.STmodel`, `createSTmodel`, `estimate.STmodel`, `estimateCV.STmodel`, `plot.STdata`, `predict.STmodel`, `print.STmodel`, `print.summary.STmodel`, `qqnorm.predCVSTmodel`, `scatterPlot.predCVSTmodel`, `simulate.STmodel`, `summary.STmodel`

Other STdata functions: `createDataMatrix`, `createSTdata`, `createSTmodel`, `detrendSTdata`, `estimateBetaFields`, `removeSTcovarMean`, `updateTrend.STdata`

### Examples

    ##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))

[Package SpatioTemporal version 1.1.9.1 Index]