predict.midas_nlpr: Predict method for non-linear parametric MIDAS regression fit
In midasr: Mixed Data Sampling Regression

Description Usage Arguments Details Value Author(s)

Predicted values based on midas_nlpr object.

1 2	## S3 method for class 'midas_nlpr' predict(object, newdata, na.action = na.omit, ...)

`object`	`midas_nlpr` object
`newdata`	a named list containing data for mixed frequencies. If omitted, the in-sample values are used.
`na.action`	function determining what should be done with missing values in `newdata`. The most likely cause of missing values is the insufficient data for the lagged variables. The default is to omit such missing values.
`...`	additional arguments, not used

predict.midas_nlpr produces predicted values, obtained by evaluating regression function in the frame newdata. This means that the appropriate model matrix is constructed using only the data in newdata. This makes this function not very convenient for forecasting purposes. If you want to supply the new data for forecasting horizon only use the function forecast.midas_r. Also this function produces only static predictions, if you want dynamic forecasts use the forecast.midas_r.

a vector of predicted values

Virmantas Kvedaras, Vaidotas Zemlys

midasr documentation built on Feb. 23, 2021, 5:11 p.m.