Module: hybrid_vector_model.statsutils

Created on 13.06.2017

@author: Samuel

Functions:

R2(predicted, observed)

anderson_darling_NB(data[, parameters, …])

global __PRESULTS global __ADRESULTS global __PSAMPLERESULTS global MAXSIZE

anderson_darling_P(data, poissonLimit, …)

anderson_darling_test_discrete(data, modelX, …)

vonmises_logpdf(x, kappa, loc, scale)

zero_truncated_NB(size, n, p[, …])

returns a sample of size “size” from the negative binomial distribution with parameters n, p under the condition that at least one element in the sample is nonzero.

R2(predicted, observed)[source]
anderson_darling_NB(data, parameters=None, poissonLimit=False, pSampleSize=0, bootstrapN=400, bootstrapN_P=0, MHSteps=100, usePreviousPVals=True, usePreviousPSamples=False, resultSaver=None)[source]

global __PRESULTS global __ADRESULTS global __PSAMPLERESULTS global MAXSIZE

anderson_darling_P(data, poissonLimit, pSampleSize, bootstrapN, bootstrapN_P, counter=None)[source]
anderson_darling_test_discrete(data, modelX, modelY, simulate_p_value=False)[source]
vonmises_logpdf(x, kappa, loc, scale)[source]
zero_truncated_NB(size, n, p, poissonLimit=False, quantile=0.999, MHSteps=100)[source]

returns a sample of size “size” from the negative binomial distribution with parameters n, p under the condition that at least one element in the sample is nonzero. MHSteps denotes the number of Metropolis-Hastings iterations