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A Comparative Study of Parametric and Nonparametric Regressions
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نویسنده
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Fattahi Shahram
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منبع
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iranian economic review - 2011 - دوره : 16 - شماره : 30 - صفحه:19 -43
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چکیده
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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).
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کلیدواژه
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ARIMA ,AM ,MARS ,PPR ,NN ,Inflation Forecast
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آدرس
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razi university, Department of Economics, ایران
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Authors
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