model_error: Error Prediction Two Variables

In nelson16silva/wavcoreinf: Estimation and Evaluation of Wavelet Core Inflation Measures

Error Prediction Two Variables

Description

This function calculates the root mean square error or mean absolute error of models estimated by the function model_fcast. This function is appropriate for forecasting evaluation of a core inflation measure that is never revised.

Usage

model_error(k, y, xreg, lags, h, RMSE = TRUE)

Arguments

k	An integer to determine the number of observations to include in the out-of-sample set.
y	A numeric vector or time series of the dependet variable; tipplically the headline inflation.
xreg	A numeric vector or time series of the independent variable; a measure of core inflation that is never revised.
lags	A data frame generated by the function lags.
h	An integer to set the desired horizon.
RMSE	Logical: if TRUE returns RMSE, if FALSE returns MAE.

Value

An integer contaning the calculated error.

See Also

model_est, model_best, model_fcast.

Examples

inf_head <- coreinf_br[["ipca"]]
inf_corems <- coreinf_br[["ipcams"]]
pq <- lags(2, 1)
model_error(24, inf_head, inf_corems, pq, 2, RMSE = TRUE)
purrr::map_dbl(1:12, ~ model_error(24, inf_head, inf_corems, pq, .x, RMSE = FALSE))

nelson16silva/wavcoreinf documentation built on Feb. 17, 2025, 7:10 p.m.