MDgof
1.1.0Various Methods for the Goodness-of-Fit Problem in D>1 Dimensions
Overview
The routine gof_test() in this package runs the goodness-of-fit test using various test statistic for multivariate data. Models under the null hypothesis can either be simple or allow for parameter estimation. p values are found via the parametric bootstrap (simulation). The routine gof_test_adjusted_pvalues() runs several tests and then finds a p value adjusted for simultaneous inference. The routine gof_power() allows the estimation of the power of the tests. hybrid_test() and hybrid_power() do the same by first generating a Monte Carlo data set under the null hypothesis and then running a number of two-sample methods. The routine run.studies() allows a user to quickly study the power of a new method and how it compares to those included in the package via a large number of case studies. For details of the methods and references see the included vignettes.
Install
Health
- OK2026-08-0513 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
- NOTE2026-08-0112 OK · 1 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
- OK2026-05-0213 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
- NOTE2026-04-2211 OK · 3 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
- ERROR2026-04-1810 OK · 3 NOTE · 0 WARNING · 1 ERROR · 0 FAILURE
Show 1 earlier snapshots
- NOTE2026-03-1011 OK · 3 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
Documentation
- Examples that run
- 100%
- Documented parameters
- 95%
- Return-value docs
- 100%
- References docs
- 0%
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Code & Tests
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Package metadata
- First published
- 2026-02-12
- Total releases
- 4 / 1 yrs
- License
- GPL (>= 2) OSI
- Minimum R
- ≥ 3.5
- Bundled data
- 31 KB / 13 files
- Download size
- 175 KB
- Installed size
- not tracked yet
- With dependencies
- not tracked yet
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