computeTestKolmogorovBeta {rotRPackage} | R Documentation |
This ROT function, called from a Test C++ object, is given a sample, a point, the necessary distribution parameters and optionnaly a test level. It then returns the result of a K-S test against the null hypothesis that the sample has un underlying Beta distribution of the given parameters and returns a list containing the result and test p-value.
computeTestKolmogorovBeta(numericalSample, r, t, a, b, testLevel = 0.95, estimatedParameters)
numericalSample |
the sample to be tested (numeric vector) |
r |
The Beta distribution rParameter. |
t |
The Beta distribution tParameter. |
a |
The Beta distribution aParameter. |
b |
The Beta distribution bParameter. |
testLevel |
the test level. (scalar in [0:1]) |
estimatedParameters |
the test level. (scalar in [0:1]) |
A list is returned, containing :
testResult |
The result. 1 means H0 is not rejected. (scalar) |
threshold |
The threshold applied to the p-value when deciding the outcome of the test. |
pValue |
The test p-value. (scalar) |
Pierre-Matthieu Pair, Softia for EDF.
# Standard Beta distribution example. (a=0, b=1) print(computeTestKolmogorovBeta(rbeta(1000, 2, 4), 2, 4, 0, 1)) print(computeTestKolmogorovBeta(rbeta(1000, 2.5, 4), 2, 4, 0, 1))