computeTestKolmogorovExponential {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 Exponential distribution of the given parameters and returns a list containing the result and test p-value.
computeTestKolmogorovExponential(numericalSample, lambda, gamma, testLevel = 0.95, estimatedParameters)
numericalSample |
the sample to be tested (numeric vector) |
lambda |
The Exponential distribution lambda. |
gamma |
The Exponential distribution gammaParameter. |
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 Exponential distribution example. print(computeTestKolmogorovExponential(rexp(1000, 3), 3, 0)) print(computeTestKolmogorovExponential(rexp(1000, 2.5), 3, 0)) # Non - Standard Exponential distribution example. print(computeTestKolmogorovExponential(rexp(1000, 3) + 1, 3, 1)) print(computeTestKolmogorovExponential(rexp(1000, 3) + 1, 3, 0.5))