Statistical Test Result #190 — Analysis Report
Contents
- glm (#190) completed
1. Glm
2026-09-21 02:16:53 · statistical_test
The glm on count completed.
| family | negative_binomial |
|---|---|
| aic | 593.503467 |
| deviance | 16.882287 |
| null_deviance | 80.057553 |
| pseudo_r2 | 0.789123 |
| n_obs | 100 |
| dispersion_phi | 0.13925 |
| deviance_gof_p | 1.0 |
| method | glm |
| value_col | count |
| significant | True |
coefficients
| term | coef | se | z | p | ci_lower | ci_upper |
|---|---|---|---|---|---|---|
| const | 0.495563 | 0.216117 | 2.293032 | 0.021846 | 0.071982 | 0.919145 |
| predictor | 0.296855 | 0.037917 | 7.828982 | 0.0 | 0.222538 | 0.371171 |
coef forest
fitted vs observed
residuals vs fitted
Method & Provenance
- Method
- Count GLM (Poisson / Negative Binomial)
- Engine
- Python · statsmodels 0.14.6
- Input dataset
- gallery — example_glm_counts.csv
- Started
- 2026-09-21 02:16:53.486314
- Permanent link
- https://cat-g-omxpert.wishartlab.com/results/by-token/d9e9c78bde024ef2898ba52fc898c183
| Parameter | Value |
|---|---|
| test_type | glm |
| value_col | count |
| predictor_cols | predictor |
Command history
# python import statsmodels.api as sm # python model = sm.GLM(y_counts, X_predictors, family=sm.families.Poisson()) # python fit = model.fit()