spm (version 1.2.2)

rfokrfidwpred: Generate spatial predictions using the average of the hybrid method of random forest and ordinary kriging and the hybrid method of random forest and inverse distance weighting (RFOKRFIDW)

Description

This function is to make spatial predictions using the average of the hybrid method of random forest and ordinary kriging and the hybrid method of random forest and inverse distance weighting (RFOKRFIDW).

Usage

rfokrfidwpred(
  longlat,
  trainx,
  trainy,
  longlatpredx,
  predx,
  mtry = function(p) max(1, floor(sqrt(p))),
  ntree = 500,
  idp = 2,
  nmaxok = 12,
  nmaxidw = 12,
  vgm.args = ("Sph"),
  block = 0,
  ...
)

Arguments

longlat

a dataframe contains longitude and latitude of point samples (i.e., trainx and trainy).

trainx

a dataframe or matrix contains columns of predictive variables.

trainy

a vector of response, must have length equal to the number of rows in trainx.

longlatpredx

a dataframe contains longitude and latitude of point locations (i.e., the centres of grids) to be predicted.

predx

a dataframe or matrix contains columns of predictive variables for the grids to be predicted.

mtry

a function of number of remaining predictor variables to use as the mtry parameter in the randomForest call.

ntree

number of trees to grow. This should not be set to too small a number, to ensure that every input row gets predicted at least a few times. By default, 500 is used.

idp

numeric; specify the inverse distance weighting power.

nmaxok

for local predicting: the number of nearest observations that should be used for a prediction or simulation, where nearest is defined in terms of the space of the spatial locations. By default, 12 observations are used for OK.

nmaxidw

for local predicting: the number of nearest observations that should be used for a prediction or simulation, where nearest is defined in terms of the space of the spatial locations. By default, 12 observations are used for IDW.

vgm.args

arguments for vgm, e.g. variogram model of response variable and anisotropy parameters. see notes vgm in gstat for details. By default, "Sph" is used.

block

block size. see krige in gstat for details.

...

other arguments passed on to randomForest or gstat.

Value

A dataframe of longitude, latitude, predictions and variances. The variances are the same as the variances of rfokpred.

References

Liaw, A. and M. Wiener (2002). Classification and Regression by randomForest. R News 2(3), 18-22.

Examples

# NOT RUN {
data(petrel)
data(petrel.grid)
rfokrfidwpred1 <- rfokrfidwpred(petrel[, c(1,2)], petrel[, c(1,2, 6:9)],
petrel[, 3], petrel.grid[, c(1,2)], petrel.grid, ntree = 500, idp = 2,
nmaxok = 12, nmaxidw = 12)
names(rfokrfidwpred1)
# }
# NOT RUN {
# }