computeTestPartialRegression {rotRPackage} | R Documentation |
This ROT function, called from a Test C++ object, is given 2 samples, a selection and optionnaly a test level. It then computes the result of a regression test against the null hypothesis that the selected linear regression coefficients are significant. It returns the test result for each selected X variable, the statistics and the p-values.
computeTestPartialRegression(outSample, inSample, selection, testLevel = 0.95)
outSample |
The 'out' sample. (n vector) |
inSample |
The 'in' sample (m-by-n matrix). |
selection |
The partial variable selection (vector of column indexes) |
testLevel |
the test level. (scalar in [0:1]) |
A list is returned, containing :
testResult |
The result. 1 means H0 is not rejected. (vector) |
threshold |
The threshold applied to the p-value when deciding the outcome of the test. |
pValues |
The test pValues. (vector) |
Pierre-Matthieu Pair, Softia for EDF.
outSample=iris[1:50,1] inSample=as.matrix(iris[1:50,2:4]) computeTestPartialRegression(outSample, inSample, c(1,2))