fun.diag2: Diagnostic function for empirical data distribution fits...

In GLDEX: Fitting Single and Mixture of Generalised Lambda Distributions

Diagnostic function for empirical data 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 an empirical data. It is also tailored for output obtained from the fun.data.fit.ml function.

Usage

fun.diag2(result, data, no.test = 1000, len=100, alpha = 0.05)

Arguments

result	Output from fun.data.fit.ml function.
data	Observations in which the distribution was fitted upon.
no.test	Number of times to do the KS tests.
len	Number of observations to sample from the data. This is also the number of observations sampled from the fitted distribution in each KS test.
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.diag1, fun.diag.ks.g, fun.diag.ks.g.bimodal

Examples

# Fits a Normal 3,2 distribution:
 junk<-rnorm(1000,3,2)
 fit<-fun.data.fit.ml(junk)

# Compute the resample K-S test results.
 fun.diag2(fit,junk)

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