ISSN:
1432-1343
Keywords:
Cluster analysis
;
Multiple regression
;
Maximum likelihood estimation
;
E-M algorithm
;
Marketing trade shows
Source:
Springer Online Journal Archives 1860-2000
Topics:
Mathematics
Notes:
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.
Type of Medium:
Electronic Resource
URL:
http://dx.doi.org/10.1007/BF01897167
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