pearsonFitM {PearsonDS}R Documentation

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 exaktly (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 martin.becker@mx.uni-saarland.de

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

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)

[Package PearsonDS version 0.91 Index]