MUVR2 (version 0.1.0)

H0_test: Perform permutation or resampling tests

Description

This function will extract data and parameter settings from a MUVR object and run standard permutation or resampling test. This will fit a standard case of multivariate predictive modelling in either a regression, classification or multilevel case. However, if an analysis has a complex sample dependency which requires constrained permutation of your response vector or if a variable pre-selection is performed for decreased computational burden, then permutaion/resampling loops should be constructed manually. In those cases, View(H0_test) can be a first start from which to build custom solutions for permutation analysis.

Usage

H0_test(
  MUVRclassObject,
  n = 50,
  nRep,
  nOuter,
  varRatio,
  parallel,
  type = c("resampling", "permutation")
)

Value

permutation_output: A permutation matrix with permuted fitness statistics (nrow=n and ncol=3 for min/mid/max)

Arguments

MUVRclassObject

a 'MUVR' class object

n

number of permutations to run

nRep

number of repetitions for each permutation (defaults to value of actual model)

nOuter

number of outer validation segments for each permutation (defaults to value of actual model)

varRatio

varRatio for each permutation (defaults to value of actual model)

parallel

whether to run calculations using parallel processing which requires registered backend (defaults to parallelization for the actual model)

type

either permutation or resampling, to decide whether the permutation sampling is performed on original Y values or the probability(If Y categorical)/distributions(If Y continuous) of Y values

Examples

# \donttest{
data("freelive2")
nRep <- 2
nOuter <- 4
varRatio <-0.6
regrModel <- MUVR2(X = XRVIP2,
                   Y = YR2,
                   nRep = nRep,
                  nOuter = nOuter,
                   varRatio = varRatio,
                   method = "PLS",
                   modReturn = TRUE)
H0_test(regrModel)
# }