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• W2023689787 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." @default.
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• W2023689787 date "1988-09-01" @default.
• W2023689787 modified "2023-09-27" @default.
• W2023689787 title "A maximum likelihood methodology for clusterwise linear regression" @default.
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• W2023689787 doi "https://doi.org/10.1007/bf01897167" @default.
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