 Multivariate Weibull mixtures with proportional hazard restrictions for dwell‐time‐based session clustering with incomplete dataPatrick Mair and Marcus Hudec Journal of the Royal Statistical Society Series C, 2009, vol. 58, issue 5, 619-639 Abstract: Summary. Emanating from classical Weibull mixture models we propose a framework for clustering survival data with various more parsimonious models by imposing restrictions on the distributional parameters. We show that these restrictions on the Weibull mixtures correspond to different proportional hazard restrictions across mixture components and Web page areas. A parametric cluster approach based on the EM algorithm is carried out on a multivariate data set. Our model set‐up encompasses incomplete‐data structures as well as censoring observations. We apply the methodology on retail data stemming from a global e‐commerce company. Sessions are clustered with respect to the dwell times that a user spends on certain page areas. The cluster solution that is found allows for a detailed examination of the navigation behaviour in terms of the hazard and survivor functions within each component. Date: 2009 Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:bla:jorssc:v:58:y:2009:i:5:p:619-639 Ordering information: This journal article can be ordered from Access Statistics for this article Journal of the Royal Statistical Society Series C is currently edited by R. Chandler and P. W. F. Smith More articles in Journal of the Royal Statistical Society Series C from Royal Statistical Society Contact information at EDIRC. |
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