GLDEX (version 2.0.0.9.3)

fun.diag2: 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)

Value

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

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.

Author

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

# \donttest{
# 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)
# }