| Type: | Package |
| Title: | Khmaladze Martingale Transformation Goodness-of-Fit Test |
| Version: | 2.3.1 |
| Description: | Consider a goodness-of-fit (GOF) problem of testing whether a random sample comes from one sample location-scale model where location and scale parameters are unknown. It is well known that Khmaladze martingale transformation method proposed by Khmaladze (1981) <doi:10.1137/1126027> provides asymptotic distribution free test for the GOF problem. This package provides test statistic and critical value of GOF test for normal, Cauchy, and logistic distributions. This package used the main algorithm proposed by Kim (2020) <doi:10.1007/s00180-020-00971-7> and tests for other distributions will be available at the later version. |
| License: | GPL-2 |
| Encoding: | UTF-8 |
| Depends: | R (≥ 2.10) |
| Imports: | Rcpp (≥ 1.0.10), ggplot2, stats, utils, Rsolnp |
| LinkingTo: | Rcpp, RcppArmadillo |
| RoxygenNote: | 7.3.2 |
| NeedsCompilation: | yes |
| Packaged: | 2025-12-18 22:25:22 UTC; ji_wo |
| Author: | Jiwoong Kim [aut, cre] |
| Maintainer: | Jiwoong Kim <jwboys26@gmail.com> |
| Repository: | CRAN |
| Date/Publication: | 2025-12-18 22:40:02 UTC |
Implementing Khmaladze Martingale Transformation.
Description
Performs goodness-of-fit test through Khmaladze matringale transformation
Usage
Run_KMT(
X,
strDistr = "Normal",
bEstimation = FALSE,
bFast_Estimation = FALSE,
bParallel = FALSE,
nThreads = 16
)
Arguments
X |
a random sample of n observations |
strDistr |
a null distribution for the hypothesis test: Normal, Cauchy, Logistic, or Gumbel. |
bEstimation |
a logical value which specifies whether or not to estimate parameters. The default value is TRUE. For FALSE, ( |
bFast_Estimation |
a logical value which specifies whether or not to use the maximum likelihood estimator ( |
bParallel |
a logical value which specifies whether or not to use the parallel computing. The default value is FALSE. |
nThreads |
the number of threads when bParallel is TRUE. The default value is 16. |
Value
A list of the following values:
- opt_x
opt.x is the value of x where the optimum of the objective function - which is also the test statistic - occurs.
- test_stat
test.stat is the test statistic obtained through Khmaladze martingale transformation.
- mu
the point estimate for the location parameter mu
- sigma
the point estimate for the scale parameter sigma
References
[1] Khmaladze, E.V., Koul, H.L. (2004). Martingale transforms goodness-of-fit tests in regression models. Ann. Statist., 32. 995-1034
[2] E.V. Khmaladze, H.L. Koul (2009). Goodness-of-fit problem for errors in nonparametric regression: distribution free approach. Ann. Statist., 37(6A) 3165-3185.
[3] Kim, Jiwoong (2020). Implementation of a goodness-of-fit test through Khmaladze martingale transformation. Comp. Stat., 35(4): 1993-2017
Examples
####################
n=20
mu0=2; sigma0=1
X = rnorm(n, mu0, sigma0)
Run_KMT(X, strDistr="Normal")