RMSPERoot Mean Square Prediction Error
RMSPERoot Mean Square Percentage Error
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Moreover, the difference in performance between the RW and CBO projections for the most recent period is statistically significant at the 5 percent significance level for the MAPE and statistically significant at a slightly higher significance level for the RMSPE.
The RMSPE of the forecast is 517%, and the proportion of the error due to systematic bias is 71%.
13) In no country was actual per capita income growth close to being as high as simulated growth, and the RMSPE of the individual forecasts ranges from 106% to more than 3000% (in the Bolivian case).
Based on my definition of an underachiever as a country whose simulated growth has an RMSPE greater than 50% (and more than 50% of the forecast error is due to systematic bias), all of the countries in my sample are growing more slowly than their factor accumulation would predict.
No country has an RMSPE of below 50%; the only country with a bias score of less than 50% (Argentina, with 14%) also has an RMSPE of 78.
For each line, the summary statistics from the forecasts were compared, using the weighted moving averages and choosing [alpha] based on the minimum RMSPE criterion.
3, the weighted moving average method resulted in smaller MAE, MAPE, SDPE and RMSPE for PAL and WCP from estimated loss ratios and derived normal losses.
To illustrate the estimation results obtained from using the weighted moving averages and setting [alpha] according to the RMSPE criterion, in panels 1.
3 results in smaller MAPE and RMSPE for PAD, HMP, FMP, and WCP.
The RMSPE can be partitioned in many different ways to identify systematic problems with models (Kohn et al.
As a summary measure of the relative degree of deviation, either mean bias or RMSPE can be used (Chaves et al.
The RMSPE analysis provided more accurate interpretation of the predicted values; for example, as a component by RMSPE analysis, mean bias from all six models were statistically significant from zero, again indicating the inaccuracy of all of the models (Table 7).