computeLinearModel {rotRPackage} | R Documentation |
This ROT function, called from a LinearModelFactory, is given two samples and a confidence level, and is used to compute a linear model. It returns the parameter estimates, confidence intervals and p-values.
computeLinearModel(x, y, testLevel = 0.95)
x |
A m-by-n matrix containing the explanatory variables. |
y |
A n-by-1 vector containng the response variables. |
testLevel |
the test level. (scalar in [0:1]) |
A list is returned, containing :
parameterEstimate |
The estimated parameters (vector). |
confidenceIntervalLow |
The parameters confidence interval lower bounds (vector). |
confidenceIntervalHigh |
The parameters confidence interval lower bounds (vector). |
pValues |
The parameters p-values. |
Pierre-Matthieu Pair, Softia for EDF.
x <- matrix(runif(40), 10, 4) r <- matrix(c(1,2,3,4), 4, 1) y <- x computeLinearModel(x,y)