Adjusting Choice Models to Better Predict Market Behavior

The emergence of Bayesian methodology has facilitated respondent-level conjoint models, and deriving utilities from choice experiments has become very popular among those modeling product line decisions or new product introductions. This review begins with a paradox of why experimental choices should mirror market behavior despite clear differences in content, structure and motivation. It then addresses ways to design the choice tasks so that they are more likely to reflect market choices. Finally, it examines ways to model the results of the choice experiments to better mirror both underlying decision processes and potential market choices.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/47012/1/11002_2005_Article_5885.pd

Some alternatives to exponential smoothing in demand forecasting

The report contains a study devoted to a comparison of exponential smoothing with other alternatives to demand forecasting. Special attention is paid to the stock-out risks assumed whenever reorder levels are set using the various methods being compared. Models presently used by NavSup are employed in order that the results be applicable to the system in use. Simulation techniques are used for drawing comparisons. For constant mean, normal demand, it is shown that exponential smoothing does not produce as accurate results as ordinary maximum likelihood techniques. For the case of a linear mean changing with time, it is shown that the two methods are about comparable. Finally, a sequential Bayes forecasting method is defined and found to compare quite favorably with exponential smoothing. The need for additional study of Bayesian methods is established. (Author)supported by the Research and Development Division, Naval Supply Systems Commandhttp://archive.org/details/somealternatives00zeh

Tables of common probability distributions

Tables that are available for certain probability distributions are limited in percentage values or parameter values. This report makes available additional such values for several probability distributions that occur in common practice.http://archive.org/details/tablesofcommonpr00zeh

Some remarks on exponential smoothing

A critical analysis of the technique of exponential smoothing as a demand forecasting tool in inventory theory. Certain standard formulas which have been developed for this technique are shown to be only asymptotically valid and therefore suspect when the number of demand periods is small. Alternate formulas, valid for any number of time periods, are derived for one special case that is commonly treated. Certain statistical weaknesses of this forecasting technique are then analyzed and, in particular, the use of mean absolute deviation to estimate variability is criticized.NAhttp://archive.org/details/someremarksonexp03zeh

HP-41C programs and instructions for probability and statistics

A compendium of programs and instructions to solve problems typically encountered in probability and statistics. Programs are designed to operate directly on the HP-41C family of hand-held calculators.Naval Postgraduate School, Monterey, Cahttp://archive.org/details/hp41cprogramsins00zehnN

Comparing inventory demand forecasts

Continued efforts to compare exponential smoothing with other alternatives to demand forecasting are summarized. Using stock-out risk at one extreme and oversupply at the other, the effects of variability in forecasting, even when accurate with respect to the mean, are highlighted. Using a normal model, exponential smoothing is identified as a major source of variability. Various forecast methods are compared using simulation relative to mean squared error when mean demand is allowed to vary according to specified patterns. In almost all circumstances, exponential smoothing consistently emerges as a first choice. The same alternatives are compared using real demand data and the results show exponential smoothing and maximum likelihood to be essentially equivalentsupported by the Research and Development Division, Naval Supply Systems Command, Washington, D. Chttp://archive.org/details/comparinginvento00zehnN0002375WR59029N

Solutions in Hadley-Whitin Q-r Models

The Hadley-Whitin approximate Q-r models have been in existence for nearly fifteen years now and are rather Widely used by practitioners because of their simplicity and rather general applicability. There are, however, some questions regarding the characterization of solutions in these models due to the fact that the objective function is not always convex as asserted by the authors. This paper gives a complete characterization of the solutions in both the backorders model and the lost sales case for normal leadtime demand. It brings out the fact that the solution always exists in both cases but may in fact be different from the published one. A simple scheme is provided for isolating the solution in terms of the given values of the parameters for any particular application.Office of Naval ResearchApproved for public release; distribution is unlimited

Estimating mean reliability growth

A model is defined wherein corrective action may be accounted for in improving the estimation of reliability over the usual nominal success ratio. Probabilities for correcting any one of K failure modes which may arise are assumed known within the structure of a multinomial sampling procedure. Mean reliability is defined as a function of the unknown probabilities attached to the failure modes, the problem being to estimate this mean. Other measures of current reliability are defined. Three different estimators of mean reliability are defined and analyzed from the point of view of unbiasedness. Explicit expressions for the bias are derived and compared numerically for a wide variety of choices for the unknown parameters. Several problem areas for further research are identified and partial formulations of some of these are discussed.Special Projects, Code SP-114http://archive.org/details/estimatingmeanre00zeh

Forecasting errors using MAD

The paper is a study of the effects of using mean absolute deviation (MAD) to estimate variability in setting reorder levels for the inventory of a stock item. The method presently employed by NavSup in setting such reorder levels involves exponentially smoothed estimates of the mean and variance of the demand process. Any error involved in setting reorder levels results in a change in the underlying risk which in turn can be translated into costs. Such errors for the method of estimation presently employed are compared with standard maximum likelihood procedures. By simulating several normal systems, the smoothing technique is found to be inferior to classical methods with no reduction in computational difficulties. (Author)A study of the effects of using mean absolute deviation (MAD) to estimate variability in setting reorder levels f~>r the inventory of a stock item. The method presently employed by NavSup in setting such reorder levels involves exponentially smoothed estimates of the mean and variance of the demand process. Any error involved in setting reorder levels results in a change in the underlying risk which in turn can be translated into costs. Such errors for the method of estimation presently employed are compared with standard maximum likelihood procedures. By simulating several normal systems, the smoothing technique is found to be inferior to classical methods with no reduction in computational difficulties.This task was supported by the Research and Development Division, Naval Supply Systems Command under NAVSUP RDT&B task area No. TF 015-02-101.http://archive.org/details/forecastingerror00zehnN