Forecasting the Penetration of a New Product--A Bayesian Approach.
We adopt a Bayesian approach to forecast the penetration of a new product into a market. We incorporate prior information from an existing product and/or management judgments into the data analysis. The penetration curve is assumed to be a nondecreasing function of time and may be under shape constraints. Markov-chain Monte Carlo methods are proposed and used to compute the Bayesian forecasts. An example on forecasting the penetration of color television using the information from black-and-white television is provided. The models considered can also be used to address the general bioassay and reliability stress-testing problems.
Year of publication: |
2000
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Authors: | Pammer, Scott E ; Fong, Duncan K H ; Arnold, Steven F |
Published in: |
Journal of Business & Economic Statistics. - American Statistical Association. - Vol. 18.2000, 4, p. 428-35
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Publisher: |
American Statistical Association |
Saved in:
Saved in favorites
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