fun.diag1 {GLDEX} | R Documentation |
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 |
test |
Simulated observations from theoretical distribution, the length
should be no.test |
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))