statsmodels.discrete.truncated_model.TruncatedLFNegativeBinomialP.predict

TruncatedLFNegativeBinomialP.predict(params, exog=None, exposure=None, offset=None, which='mean', y_values=None)

Predict response variable or other statistic given exogenous variables.

Parameters:
paramsarray_like

The parameters of the model.

exogndarray, optional

Explanatory variables for the main count model. If exog is None, then the data from the model will be used.

offsetndarray, optional

Offset is added to the linear predictor of the mean function with coefficient equal to 1. Default is zero if exog is not None, and the model offset if exog is None.

exposurendarray, optional

Log(exposure) is added to the linear predictor with coefficient equal to 1. If exposure is specified, then it will be logged by the method. The user does not need to log it first. Default is one if exog is is not None, and it is the model exposure if exog is None.

whichstr (optional)

Statitistic to predict. Default is ‘mean’.

  • ‘mean’ : the conditional expectation of endog E(y | x)

  • ‘mean-main’ : mean parameter of truncated count model. Note, this is not the mean of the truncated distribution.

  • ‘linear’ : the linear predictor of the truncated count model.

  • ‘var’ : returns the estimated variance of endog implied by the model.

  • ‘prob-trunc’ : probability of truncation. This is the probability of observing a zero count implied by the truncation model.

  • ‘prob’ : probabilities of each count from 0 to max(endog), or for y_values if those are provided. This is a multivariate return (2-dim when predicting for several observations). The probabilities in the truncated region are zero.

  • ‘prob-base’ : probabilities for untruncated base distribution. The probabilities are for each count from 0 to max(endog), or for y_values if those are provided. This is a multivariate return (2-dim when predicting for several observations).

y_valuesarray_like

Values of the random variable endog at which pmf is evaluated. Only used if which="prob"

Returns:
predicted values

Notes

If exposure is specified, then it will be logged by the method. The user does not need to log it first.

Last update: Oct 03, 2024