pearsonFitM: Method of Moments Estimator for Pearson Distributions

In PearsonDS: Pearson Distribution System

Method of Moments Estimator for Pearson Distributions

Description

This function calculates the method of moments estimator for Pearson distribution, ie, it generates a Pearson distribution with moments exactly (up to rounding errors) matching the input moments mean, variance, skewness and kurtosis.

Usage

pearsonFitM(mean, variance, skewness, kurtosis, moments)

Arguments

mean	target mean.
variance	target variance.
skewness	target skewness.
kurtosis	target kurtosis (not excess kurtosis!).
moments	optional vector/list of mean, variance, skewness, kurtosis (not excess kurtosis) in this order. Overrides all other input parameters, if given.

Value

List of parameters for Pearson distribution. First entry gives type of distribution (0 for type 0, 1 for type I, ..., 7 for type VII), remaining entries give distribution parameters (depending on distribution type).

Author(s)

Martin Becker [e-mail]

References

[1] Johnson, N. L., Kotz, S. and Balakrishnan, N. (1994) Continuous Univariate Distributions, Vol. 1, Wiley Series in Probability and Mathematical Statistics, Wiley

[2] Johnson, N. L., Kotz, S. and Balakrishnan, N. (1994) Continuous Univariate Distributions, Vol. 2, Wiley Series in Probability and Mathematical Statistics, Wiley

See Also

PearsonDS-package, Pearson, pearsonFitML, pearsonMoments, pearsonMSC

Examples

## Define moments of distribution
moments <- c(mean=1,variance=2,skewness=1,kurtosis=5)
## find Pearson distribution with these parameters
ppar <- pearsonFitM(moments=moments)
print(unlist(ppar))
## check moments
pearsonMoments(params=ppar)

PearsonDS documentation built on Aug. 12, 2023, 5:14 p.m.