rfpred function

Generate spatial predictions using random forest (RF)

This function is to make spatial predictions using random forest.

rfpred(
  trainx,
  trainy,
  longlatpredx,
  predx,
  mtry = if (!is.null(trainy) && !is.factor(trainy)) max(floor(ncol(trainx)/3), 1) else
    floor(sqrt(ncol(trainx))),
  ntree = 500,
  ...
)

Arguments

• trainx: a dataframe or matrix contains columns of predictor 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.
• ...: other arguments passed on to randomForest.

Returns

A dataframe of longitude, latitude and predictions.

Examples

## Not run:

data(petrel)
data(petrel.grid)
rfpred1 <- rfpred(petrel[, c(1,2, 6:9)], petrel[, 5], petrel.grid[, c(1,2)],
petrel.grid, ntree = 500)
names(rfpred1)
## End(Not run)

References

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

Author(s)

Jin Li