Session Clustering Using Mixtures of Proportional Hazards Models

Mair, Patrick and Hudec, Marcus (2008) Session Clustering Using Mixtures of Proportional Hazards Models. Research Report Series / Department of Statistics and Mathematics, 63. Department of Statistics and Mathematics, WU Vienna University of Economics and Business, Vienna.


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Emanating from classical Weibull mixture models we propose a framework for clustering survival data with various proportionality restrictions imposed. By introducing mixtures of Weibull proportional hazards models on a multivariate data set a parametric cluster approach based on the EM-algorithm is carried out. The problem of non-response in the data is considered. The application example is a real life data set stemming from the analysis of a world-wide operating eCommerce application. Sessions are clustered due to the dwell times a user spends on certain page-areas. The solution allows for the interpretation of the navigation behavior in terms of survival and hazard functions. A software implementation by means of an R package is provided. (author´s abstract)

Item Type: Paper
Keywords: proportional hazards models / Weibull mixture models / EM-algorithm / incomplete data / Web usage mining
Divisions: Departments > Finance, Accounting and Statistics > Statistics and Mathematics
Depositing User: Repository Administrator
Date Deposited: 25 Mar 2008 01:53
Last Modified: 22 Oct 2019 00:41


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