computeTestKolmogorovTriangular {rotRPackage}R Documentation

Compute the Kolmogorov-Smirnoff test on a Triangular Distribution sample.

Description

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 Triangular distribution of the given parameters and returns a list containing the result and test p-value.

Usage

computeTestKolmogorovTriangular(numericalSample, a, m,
b, testLevel = 0.95, estimatedParameters)

Arguments

numericalSample the sample to be tested (numeric vector)
a The Triangular distribution aParameter.
m The Triangular distribution bParameter.
b The Triangular distribution mParameter.
testLevel the test level. (scalar in [0:1])
estimatedParameters the test level. (scalar in [0:1])

Value

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)

Author(s)

Pierre-Matthieu Pair, Softia for EDF.

Examples

# Standard Triangular distribution example.
a <- -1.0
m <- 2.0
b <- 6.0
point <- runif(1000)
sample <- ifelse(point < (m - a) / (b - a), a + sqrt(point * (b - a) *
(m - a)), b - sqrt((1.0 - point) * (b - a) * (b - m))) 
print(computeTestKolmogorovTriangular(sample, -1, 2, 6))
print(computeTestKolmogorovTriangular(sample, -1, 1.5, 6))

[Package rotRPackage version 1.4.3 Index]