Many economic and business problems require a set of random variates from the posterior density of the unknown parameters. The set of random variates can be used to integrate numerically many forms of functions. Since a closed form of the posterior density of models in time series analysis is...

This is a study of forecasting models that aggregate monthly times series into bimonthly and quarterly models using the 1,428 seasonal monthly series of the M3 competition of Makridakis and Hibon (2000). These aggregating models are used to answer the question of whether aggregation models of...

Assume that we generate forecasts from a model y=cx+d+. “c” and “d” are placement parameters estimated from observations on x and y, and is the residual. If the residual is observed to be symmetric about the mode, it is usually assumed to be distributed by the Gaussian family of...

This chapter shows how the forecasting and the planning functions in a supply chain can be organized so they will yield optimal forecasts for an entire supply chain. We achieve this result by replacing the process of generating forecasts with that of making optimal coordinated supply chain...

In this chapter, we describe how time series analysis can often provide better insight than prior year data for predicting the total impact of an atypical event – including (1) taking into account other atypical events, (2) determining if the impact lasted greater than one season, and (3)...

Production operations managers have long been concerned about new product development and the life cycle of these products. Because many products do not sell at constant levels throughout their lives, product life cycles (PLCs) must be considered when developing sales forecasts. Innovation...

Many forecasting methodologies used in the new product development process are superficial techniques that either fail to incorporate the voice of the consumer or only touch on superficial consumer attitudes while completely ignoring the affectively laden hedonic aspects of consumption. This...

When forecasting intermittent demand the method derived by Croston (1972) is often cited. Previous research favorably compared Croston's forecasting method for demand with simple exponential smoothing assuming a nonzero demand occurs as a Bernoulli process with a constant probability. In...