fun.diag1: Diagnostic function for theoretical distribution fits through...

In GLDEX: Fitting Single and Mixture of Generalised Lambda Distributions

Diagnostic function for theoretical distribution fits through the resample Kolmogorov-Smirnoff tests

Description

This function is primarily designed to be used for testing the fitted distribution with reference to a theoretical distribution. It is also tailored for output obtained from the fun.data.fit.ml function.

Usage

fun.diag1(result, test, no.test = 1000, alpha = 0.05)

Arguments

result	Output from fun.data.fit.ml function.
test	Simulated observations from theoretical distribution, the length should be no.test\mbox{\textasciitilde}2.
no.test	Number of times to do the KS tests.
alpha	Significance level of KS test.

Value

A vector showing the number of times the KS p-value is greater than alpha for each of the distribution fit strategy.

Note

If there are ties, jittering is used in ks.gof.

Author(s)

Steve Su

References

Su, S. (2005). A Discretized Approach to Flexibly Fit Generalized Lambda Distributions to Data. Journal of Modern Applied Statistical Methods (November): 408-424.

Su, S. (2007). Numerical Maximum Log Likelihood Estimation for Generalized Lambda Distributions. Journal of Computational statistics and data analysis 51(8) 3983-3998.

Su (2007). Fitting Single and Mixture of Generalized Lambda Distributions to Data via Discretized and Maximum Likelihood Methods: GLDEX in R. Journal of Statistical Software: *21* 9.

See Also

fun.diag2, fun.diag.ks.g, fun.diag.ks.g.bimodal

Examples

# Fits a Weibull 5,2 distribution:
 weibull.approx.ml<-fun.data.fit.ml(rweibull(1000,5,2))

# Compute the resample K-S test results.
 fun.diag1(weibull.approx.ml, rweibull(100000, 5, 2))

GLDEX documentation built on Aug. 21, 2023, 9:08 a.m.