Backtest measures for Dynamic Model Averaging and comparison with Dynamic Model Selection
Backtest measures for Dynamic Model Averaging and comparison with Dynamic Model Selection. This function evaluate the out of sample performance of DMA and compare it with DMS.
an object of the class DMA-class, created using the function DMA.
An integer indicating the length of the burn-in period. By default
The function returns a
matrix with Mean Square 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
Leopoldo Catania & Nima Nonejad
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## Not run: 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) ## End(Not run)
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