Title of article :
A Comparative Study of Parametric and Nonparametric Regressions
Author/Authors :
Fattahi, Shahram razi university - Department of Economics, كرمانشاه, ايران
From page :
19
To page :
43
Abstract :
This paper evaluates inflation forecasts made by parametric and nonparametric models. The results revealed that the neural network model yields better estimates of inflation rate than do parametric autoregressive integrated moving average (ARIMA) and linear models. Furthermore, the neural network model outperformed nonparametric models (except MARS).
Keywords :
ARIMA , AM , MARS , PPR , NN , Inflation Forecast
Journal title :
Iranian Economic Review (IER)
Journal title :
Iranian Economic Review (IER)
Record number :
2567520
Link To Document :
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