BacktestDMA: Backtest measures for Dynamic Model Averaging and comparison...
In LeopoldoCatania/eDMA: Dynamic Model Averaging with Grid Search

Description Usage Arguments Details Value Author(s) Examples

Backtest measures for Dynamic Model Averaging and comparison with Dynamic Model Selection. This function evaluates the out of sample performance of DMA and compare it with DMS.

1	BacktestDMA(object, iBurnPeriod = NULL)

`object`	an object of the class DMA-class, created using the function DMA.
`iBurnPeriod`	An integer indicating the length of the burn-in period. By default `iBurnPeriod = NULL`. If `iBurnPeriod = NULL` then one third of the total sample is used as the burn-in in period and a warning is printed.

The function returns a matrix with Mean Squared Error (MSE), Mean Absolute Error (MAD) and Predictive Likelihood for DMA and DMS using the predictions during the out-of-sample period.

An object of the class matrix.

Leopoldo Catania & Nima Nonejad

library(eDMA)

## load data
data("USData")

## do DMA, keep the first three predictors fixed and the intercept
Fit <- DMA(GDPDEF ~ Lag(GDPDEF, 1) + Lag(GDPDEF, 2) + Lag(GDPDEF, 3) +
            Lag(ROUTP, 1) + Lag(UNEMP, 1), data = USData, vDelta = c(0.9, 0.95, 0.99),
            vKeep = c(1, 2, 3))

BacktestDMA(Fit, iBurnPeriod = 32)