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  • Maximum likelihood estimation  (2)
  • Game Theory  (1)
  • 1
    Digitale Medien
    Digitale Medien
    Springer
    Marketing letters 4 (1993), S. 337-348 
    ISSN: 1573-059X
    Schlagwort(e): Product Design ; Product Competition ; Conjoint Analysis ; Game Theory
    Quelle: Springer Online Journal Archives 1860-2000
    Thema: Wirtschaftswissenschaften
    Notizen: Abstract While conjoint analysis has been applied in a wide variety of different contexts in Marketing, most applications fail to explicitly consider retaliatory reactions from competitors. In this paper, a methodological extension is developed for conjoint analysis by explicitly modeling competition in a game theoretic context. The Nash equilibrium concept is employed to model competitive reactions to produce design, and its implications for reactive product strategies are discussed. The optimal product design problem for each firm is formulated as a nonlinear integer programming problem, which is solved via a specialized branch and bound method combined with a heuristic. In order to compute a Nash equilibrium, a sequential iterative procedure is proposed. The proposed procedure is illustrated under several scenarios of competition using previously published conjoint data.
    Materialart: Digitale Medien
    Standort Signatur Erwartet Verfügbarkeit
    BibTip Andere fanden auch interessant ...
  • 2
    Digitale Medien
    Digitale Medien
    Springer
    Journal of classification 12 (1995), S. 21-55 
    ISSN: 1432-1343
    Schlagwort(e): Mixture models ; Generalized linear models ; EM algorithm ; Maximum likelihood estimation
    Quelle: Springer Online Journal Archives 1860-2000
    Thema: Mathematik
    Notizen: Abstract A mixture model approach is developed that simultaneously estimates the posterior membership probabilities of observations to a number of unobservable groups or latent classes, and the parameters of a generalized linear model which relates the observations, distributed according to some member of the exponential family, to a set of specified covariates within each Class. We demonstrate how this approach handles many of the existing latent class regression procedures as special cases, as well as a host of other parametric specifications in the exponential family heretofore not mentioned in the latent class literature. As such we generalize the McCullagh and Nelder approach to a latent class framework. The parameters are estimated using maximum likelihood, and an EM algorithm for estimation is provided. A Monte Carlo study of the performance of the algorithm for several distributions is provided, and the model is illustrated in two empirical applications.
    Materialart: Digitale Medien
    Standort Signatur Erwartet Verfügbarkeit
    BibTip Andere fanden auch interessant ...
  • 3
    Digitale Medien
    Digitale Medien
    Springer
    Journal of classification 5 (1988), S. 249-282 
    ISSN: 1432-1343
    Schlagwort(e): Cluster analysis ; Multiple regression ; Maximum likelihood estimation ; E-M algorithm ; Marketing trade shows
    Quelle: Springer Online Journal Archives 1860-2000
    Thema: Mathematik
    Notizen: Abstract This paper presents a conditional mixture, maximum likelihood methodology for performing clusterwise linear regression. This new methodology simultaneously estimates separate regression functions and membership inK clusters or groups. A review of related procedures is discussed with an associated critique. The conditional mixture, maximum likelihood methodology is introduced together with the E-M algorithm utilized for parameter estimation. A Monte Carlo analysis is performed via a fractional factorial design to examine the performance of the procedure. Next, a marketing application is presented concerning the evaluations of trade show performance by senior marketing executives. Finally, other potential applications and directions for future research are identified.
    Materialart: Digitale Medien
    Standort Signatur Erwartet Verfügbarkeit
    BibTip Andere fanden auch interessant ...
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