A Comparative Study of Test Procedures uses in Assessing the Forecasting Ability of Linear Models with Applications to Crop Yield Data
AbstractThe choice of the appropriate linear model before this can be used for planning and decision making, has been the concern of many statistical workers. Most of the methods in the literature aim at evaluating the descriptive ability of the candidate models. In the present paper an evaluation scheme of the predictability of a linear model based on a function of the discrepancy of the observed and the corresponding predicted values of the dependent variable is studied. Based on this statistical function, the predictability of a linear model is tested. Considering the ratio of such functions for two linear models, the predictability of these models is compared. Applications on real and simulated data are also presented
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Bibliographic InfoPaper provided by University Library of Munich, Germany in its series MPRA Paper with number 6280.
Date of creation: 1998
Date of revision:
Linear model; Model selection; Decision making; Predictability; x^2 distribution; F distribution;
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- C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General
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