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Segmentação de Mercado e modelos mistura de regressão para variáveis normais

Author

Listed:
  • Ana Oliveira-Brochado

    (EDGE, CESUR, DECIVIL-IST, Universidade Técnica de Lisboa)

  • Francisco Vitorino Martins

    (EDGE, Faculdade de Economia da Universidade do Porto)

Abstract

The purpose of this work is to provide an overview of what is perhaps the most common analysis context in market research – that of regression models for normally distributed data. In fact, examples of applications of these models continue to accumulate in the marketing literature, given their relative advantages. Moreover, these models are ease implemented due to its incorporation in many commercial packages of marketing research. We aim at presenting the background for the development of mixture regression models (switching regressions, clusterwise regression and finite mixture models) and review the formulation of the basic model and its main extensions in the context of panel data analysis and conjoint studies.

Suggested Citation

  • Ana Oliveira-Brochado & Francisco Vitorino Martins, 2008. "Segmentação de Mercado e modelos mistura de regressão para variáveis normais," FEP Working Papers 262, Universidade do Porto, Faculdade de Economia do Porto.
  • Handle: RePEc:por:fepwps:262
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    References listed on IDEAS

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    1. Engel, Charles & Hamilton, James D, 1990. "Long Swings in the Dollar: Are They in the Data and Do Markets Know It?," American Economic Review, American Economic Association, vol. 80(4), pages 689-713, September.
    2. Hamilton, James D., 1990. "Analysis of time series subject to changes in regime," Journal of Econometrics, Elsevier, vol. 45(1-2), pages 39-70.
    3. Wayne S. DeSarbo & Kamel Jedidi & Indrajit Sinha, 2001. "Customer value analysis in a heterogeneous market," Strategic Management Journal, Wiley Blackwell, vol. 22(9), pages 845-857, September.
    4. Wayne DeSarbo & Richard Oliver & Arvind Rangaswamy, 1989. "A simulated annealing methodology for clusterwise linear regression," Psychometrika, Springer;The Psychometric Society, vol. 54(4), pages 707-736, September.
    5. Wayne DeSarbo & William Cron, 1988. "A maximum likelihood methodology for clusterwise linear regression," Journal of Classification, Springer;The Classification Society, vol. 5(2), pages 249-282, September.
    6. Michel Wedel & Wayne DeSarbo, 1995. "A mixture likelihood approach for generalized linear models," Journal of Classification, Springer;The Classification Society, vol. 12(1), pages 21-55, March.
    7. Hamilton, James D, 1991. "A Quasi-Bayesian Approach to Estimating Parameters for Mixtures of Normal Distributions," Journal of Business & Economic Statistics, American Statistical Association, vol. 9(1), pages 27-39, January.
    8. Stanley Sclove, 1987. "Application of model-selection criteria to some problems in multivariate analysis," Psychometrika, Springer;The Psychometric Society, vol. 52(3), pages 333-343, September.
    9. Hamilton, James D, 1989. "A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle," Econometrica, Econometric Society, vol. 57(2), pages 357-384, March.
    10. Cosslett, Stephen R. & Lee, Lung-Fei, 1985. "Serial correlation in latent discrete variable models," Journal of Econometrics, Elsevier, vol. 27(1), pages 79-97, January.
    11. Goldfeld, Stephen M. & Quandt, Richard E., 1973. "A Markov model for switching regressions," Journal of Econometrics, Elsevier, vol. 1(1), pages 3-15, March.
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    More about this item

    Keywords

    market segmentation; mixture regression models; normal data.;
    All these keywords.

    JEL classification:

    • C0 - Mathematical and Quantitative Methods - - General
    • D0 - Microeconomics - - General

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