ParallelDSM (version 0.3.7)

GetPredictorSubset: calculation function for cutting spatial data (tool function,Not as an open function, only for function calls)

Description

calculation function for cutting spatial data (tool function,Not as an open function, only for function calls)

Usage

GetPredictorSubset(
  predictor.name,
  iblock,
  nblock,
  fn,
  nr,
  nc,
  resolutions,
  pro,
  from,
  to
)

Value

Parallel calculation of the cut part of the data box data

Arguments

predictor.name

: the name of the predictor variable

iblock

: sequence code of parallel computing

nblock

: number of target blocks (integer)

fn

: The passed value of a global variable

nr

: The passed value of a global variable

nc

: The passed value of a global variable

resolutions

: The passed value of a global variable

pro

: The passed value of a global variable

from

: Which row to start cutting the matrix

to

: Where does the last row of the cut matrix go

References

Breiman, L. (2001). Random forests. Mach. Learn. 45, 5–32. Meinshausen, N. (2006) "Quantile Regression Forests", Journal of Machine Learning Research 7, 983-999 http://jmlr.csail.mit.edu/papers/v7/

Examples

# \donttest{
GetPredictorSubset("dem",4,10,"covariate",486,777,NULL,NULL,1,10)
# }