This is a test framework for goodness-of-fit statistic tests.
Framework consists of 5 modules
- Core module - provides distributions, cdf, pdf etc.
- Persistence module - provides different stores to store data.
- Experiment module - provides pipeline for experiment and default components for pipeline.
- Expert system module - provides expert system for goodness-of-fit testing.
- Tests module - provides different goodness-of-fit tests.
CriticalValueSqLiteStore - store critical values and target distributions in SQLite.
CriticalValueFileStore - store critical values and target distributions in JSON and CSV.
RvsSqLiteStore - store generated rvs in SQLite.
RvsFileStore - store generated rvs in CSV.
PowerResultSqLiteStore - store PowerCalculationWorker result in SQLite
PowerCalculationWorker - calculates goodness-of-fit test power
№ | Test | Status |
---|---|---|
1 | Anderson–Darling | Done |
2 | Chi square | Done |
3 | Kolmogorov–Smirnov | Done |
4 | Lilliefors | Done |
5 | Cramér–von Mises | Done |
6 | Min-Toshiyuki | Done |
7 | Smith and Brian | Done |
8 | Ozturk and Korukoglu | Done |
9 | Tiku-Singh | Done |
10 | Lockhart-O'Reilly-Stephens | Done |
11 | Mann-Scheuer-Fertig | Done |
12 | Evans, Johnson and Green | Done |
13 | Skewness | Done |
14 | Kurtosis | Done |
15 | Statistic based on stabilized probability plot | Done |
16 | Test statistic of Shapiro Wilk | Done |
Test | Second Header |
---|---|
Ozturk and Korukoglu | Content Cell |
Jackson | Content Cell |
Lewis | Content Cell |
Test | Second Header |
---|---|
Anderson–Darling | Content Cell |
Kolmogorov–Smirnov | Content Cell |
Chi square | Content Cell |
skewness | Content Cell |
kurtosis | Content Cell |
git clone https://github.com/PySATL/pysatl-experiment
Install dependencies:
poetry install
Install requirements
poetry install --with dev
Install pre-commit hooks:
poetry run pre-commit install
Starting manually:
poetry run pre-commit run --all-files --color always --verbose --show-diff-on-failure