Peña, Daniel; Yohai, Victor A Dirichlet random coefficient regression model for quality indicators. (English) Zbl 1077.62128 J. Stat. Plann. Inference 136, No. 3, 942-961 (2006). Summary: We present a random coefficient regression model in which a response is linearly related to some explanatory variables with random coefficients following a Dirichlet distribution. These coefficients can be interpreted as weights because they are nonnegative and add up to one. The proposed estimation procedure combines iteratively reweighted least squares and the maximization on an approximated likelihood function. We also present a diagnostic tool based on a residual Q-Q plot and two procedures for estimating individual weights. The model is used to construct an index for measuring the quality of the railroad system in Spain. Cited in 7 Documents MSC: 62P30 Applications of statistics in engineering and industry; control charts 62F10 Point estimation 62J99 Linear inference, regression Keywords:Random weights; Dirichlet distribution; Iterative least squares; Monte Carlo methods; Q-Q plot PDFBibTeX XMLCite \textit{D. Peña} and \textit{V. Yohai}, J. Stat. Plann. Inference 136, No. 3, 942--961 (2006; Zbl 1077.62128) Full Text: DOI References: [1] Allenby, G. M.; Rossi, P. E., Marketing models of consumer heterogeneity, J. Econometrics, 89, 57-78 (1999) · Zbl 0959.62116 [2] Carroll, J. D.; Green, P. E., Psychometric methods in marketing researchPart I, conjoint analysis, J. Marketing Res., XXXII, 385-391 (1995) [3] Cronin, J.; Taylor, S., Measuring service qualitya reexamination and extension, J. Marketing, 56, July, 55-68 (1992) [4] Cronin, J.; Taylor, S., SERVPERF versus SERVQUALreconciling performance-based and perceptions-minus-expectations measurement of service quality, J. 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