IV2SLS.predict(params: ArrayLike, *, exog: IVDataLike | None = None, endog: IVDataLike | None = None, data: DataFrame | None = None, eval_env: int = 4) DataFrame

Predict values for additional data

params: ArrayLike

Model parameters (nvar by 1)

exog: IVDataLike | None = None

Exogenous regressors (nobs by nexog)

endog: IVDataLike | None = None

Endogenous regressors (nobs by nendog)

data: DataFrame | None = None

Values to use when making predictions from a model constructed from a formula

eval_env: int = 4

Depth of use when evaluating formulas.


Fitted values from supplied data and parameters

Return type:



The number of parameters must satisfy nvar = nexog + nendog.

When using exog and endog, regressor matrix is constructed as [exog, endog] and so parameters must be aligned to this structure. The the the same structure used in model estimation.

If data is not none, then exog and endog must be none. Predictions from models constructed using formulas can be computed using either exog and endog, which will treat these are arrays of values corresponding to the formula-processed data, or using data which will be processed using the formula used to construct the values corresponding to the original model specification.