OPTIMAL ESTIMATION OF PARAMETERS IN MARKET RESEARCH MODELS

V. Savani
Additional contact information
V. Savani: Department of Mathematics, Cardiff University, Cardiff, CF24 4AG, U.K.

Chapter 9 in Computer Aided Methods in Optimal Design and Operations, 2006, pp 79-88 from World Scientific Publishing Co. Pte. Ltd.

Abstract: AbstractIn the modeling of market research data the so-called Gamma-Poisson model is very popular. The model fits the number of purchases of an individual product made by a random consumer. The model presumes that the number of purchases made by random households, in any time interval, follows the negative binomial distribution. The fitting of the Gamma-Poisson model requires the estimation of the mean m and shape parameter k of the negative binomial distribution. Little is known about the optimal estimation of parameters of the Gamma-Poisson model. The primary aim of this paper is to investigate the efficient estimation of these parameters.

Keywords: Optimization; Optimal Design; Global Optimization; Optimal Control (search for similar items in EconPapers)
Date: 2006
References: Add references at CitEc
Citations:

Downloads: (external link)
https://www.worldscientific.com/doi/pdf/10.1142/9789812772954_0009 (application/pdf)
https://www.worldscientific.com/doi/abs/10.1142/9789812772954_0009 (text/html)
Ebook Access is available upon purchase.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:wsi:wschap:9789812772954_0009

Ordering information: This item can be ordered from

Access Statistics for this chapter

More chapters in World Scientific Book Chapters from World Scientific Publishing Co. Pte. Ltd.
Bibliographic data for series maintained by Tai Tone Lim ().