Trend Modelling

Description

The coding of trend, in particular multivariate trends, will be described here

Details

See RFcalc, RMtrend and also the examples below for some insight on the possibilities of trend modelling.

Author(s)

Martin Schlather, schlather@math.uni-mannheim.de

See Also

RFcalc, RM, RMmodels, RMtrend, RMmodelsMultivariate

Examples

 

require(geoR)

data(ca20) ## data set from geoR
ca20.df <- as.data.frame(ca20)
head(ca20.df)
RFoptions(coordnames=c("east", "north"), varnames="data") 

## covariance model with variance, scale and nugget to be estimated;
## just to abbreviate later on
M <- RMexp(var=NA, scale=NA) + RMnugget(var=NA)
 

## short definition of a trend using the fact that ca20.df is a
## data.frame
ca20.RFmod02 <- ~ 1 + altitude + M
(ca20.fit02.RF <- RFfit(ca20.RFmod02, data=ca20.df))


## long definition, which allows also for more general constructions
ca20.RFmod02 <- NA + NA*RMcovariate(ca20.df$altitude) + M 
(ca20.fit02.RF <- RFfit(ca20.RFmod02, data=ca20.df))


## Note that the following also works.
## Here, the covariance model must be the first summand
ca20.RFmod02 <- M + NA + ca20.df$altitude 
print(ca20.fit02.RF <- RFfit(ca20.RFmod02, data=ca20.df))

### The following does NOT work, as R assumes (NA + ca20.df$altitude) + M
(ca20.RFmod02 <- NA + ca20.df$altitude + M) 
try(ca20.fit02.RF <- RFfit(ca20.RFmod02, data=ca20.df)) ### error ...


## factors:
ca20.RFmod03 <- ~ 1 + area + M ### 
(ca20.fit03.RF <- RFfit(ca20.RFmod03, data=ca20.df))