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predict.recursive

Recursive Model Predictions


Description

Make predictions from a recursive model.

Usage

## S3 method for class 'recursive'
predict(object, new_data, type = NULL, opts = list(), ...)

Arguments

object

An object of class model_fit

new_data

A rectangular data object, such as a data frame.

type

A single character value or NULL. Possible values are "numeric", "class", "prob", "conf_int", "pred_int", "quantile", or "raw". When NULL, predict() will choose an appropriate value based on the model's mode.

opts

A list of optional arguments to the underlying predict function that will be used when type = "raw". The list should not include options for the model object or the new data being predicted.

...

Arguments to the underlying model's prediction function cannot be passed here (see opts). There are some parsnip related options that can be passed, depending on the value of type. Possible arguments are:

  • level: for types of "conf_int" and "pred_int" this is the parameter for the tail area of the intervals (e.g. confidence level for confidence intervals). Default value is 0.95.

  • std_error: add the standard error of fit or prediction (on the scale of the linear predictors) for types of "conf_int" and "pred_int". Default value is FALSE.

  • quantile: the quantile(s) for quantile regression (not implemented yet)

  • time: the time(s) for hazard probability estimates (not implemented yet)

Details

Refer to recursive() for further details and examples.

Value

Numeric values for the recursive panel prediction


modeltime

The Tidymodels Extension for Time Series Modeling

v0.5.1
MIT + file LICENSE
Authors
Matt Dancho [aut, cre], Business Science [cph]
Initial release

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