| 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 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 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,
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)