Linear regression, forecasting method

Most price forecasts are based on an analysis of historic price data. Several methods are used, as illustrated in Figure 6.4. The simplest method is to use the current price, as in Figure 6.4a, but this is unsatisfactory for most commodities. Linear regression of... 

Linear regression and econometric methods are used to plan business volume for long term forecast (12 months to 5 years). 

To provide a comparison, we also evaluated forecast errors and cost for the rules used by the plarmers at this retailer, the k median method based on store descriptors, alone and combined with sales mix differences, and two standard approaches to variable selection in linear regression, since the problem of choosing k test stores and a linear prediction function based on test sales at these stores can be viewed as choosing the best k out of n possible variables in a linear regression. Given actual sales Sp and test sales Sjp for i = 1,. . . n and p = 1,. . . m, we used the forward selection and backward elimination methods (Myers (1990)) to choose k out of the n test... 

Booth, G. W., G. E. P. Box, M. E. Muller, and T. I. Peterson, Forecasting by generalized regression methods, non-linear estimation, IBM Share Program Package 687, International Business Machines Corp., New York (1958). 

From the given data, we then have n linear equations relating the actual and forecasted demands. Following the approach given in Srinivasan (2010), we can use the least square regression method to estimate the level (a) and trend (b) parameters. The unconstrained optimization problem is to determine a and b such that... 

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