Constructor
new GeneralizedLinearRegressionSummary(dataset, origModel)
Parameters:
| Name | Type | Description |
|---|---|---|
dataset |
Dataset to be summarized. | |
origModel |
Model to be summarized. This is copied to create an internal model which cannot be modified from outside. |
Methods
aic() → {double}
Akaike Information Criterion (AIC) for the fitted model.
Returns:
- Type
- double
degreesOfFreedom() → {double}
Degrees of freedom.
Returns:
- Type
- double
deviance() → {double}
The deviance for the fitted model.
Returns:
- Type
- double
dispersion() → {double}
The dispersion of the fitted model.
Returns:
- Type
- double
nullDeviance() → {double}
The deviance for the null model.
Returns:
- Type
- double
predictions() → {module:eclairjs/sql.Dataset}
Predictions output by the model's `transform` method.
Returns:
residualDegreeOfFreedom() → {int}
The residual degrees of freedom.
Returns:
- Type
- int
residualDegreeOfFreedomNull() → {int}
The residual degrees of freedom for the null model.
Returns:
- Type
- int
residuals(residualsTypeopt) → {module:eclairjs/sql.Dataset}
Get the residuals of the fitted model by type.
Parameters:
| Name | Type | Attributes | Description |
|---|---|---|---|
residualsType |
string |
<optional> |
The type of residuals which should be returned. Supported options: deviance, pearson, working and response. |