PLSroundingLoop: PLSrounding on portions of data at a time

Description

The PLSrounding runs are coordinated by using preliminary differences as input for the next run (parameter preDifference)

Usage

PLSroundingLoop(
  data,
  loopId,
  ...,
  zeroCandidates = FALSE,
  forceInner = FALSE,
  preRounded = NULL,
  plsWeights = NULL,
  printInc = TRUE,
  preDifference = TRUE,
  preOutput = NULL,
  rndSeed = 123
)

Value

As output from PLSrounding

Arguments

data: Input data as a data frame (inner cells)
loopId: Variable holding id for loops
...: PLSrounding parameters
zeroCandidates: PLSrounding parameter (see details)
forceInner: PLSrounding parameter (see details)
preRounded: PLSrounding parameter (see details)
plsWeights: PLSrounding parameter (see details)
printInc: Printing iteration information to console when TRUE
preDifference: When TRUE, the preDifference parameter to PLSrounding is used. Each time with the differences obtained so far.
preOutput: preOutput The function can continue from output from a previous run
rndSeed: If non-NULL, a random generator seed to be set locally at the beginning of PLSroundingLoop without affecting the random value stream in R. Within PLSroundingLoop, PLSrounding is called with rndSeed = NULL.

Details

Note that in this function zeroCandidates, forceInner, preRounded and plsWeights cannot be supplied as vectors. They may be specified as functions or as variables in the input data.

Examples

Run this code

mf2 <- ~region + fylke * hovedint
z2 <- SmallCountData("z2")
a <- PLSroundingLoop(z2, loopId = "kostragr", freqVar = "ant", formula = mf2)
a

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