Please use this identifier to cite or link to this item:
Title: Modelling bimodality of length of tourist stay
Authors: Gómez-Déniz, E. 
Pérez-Rodríguez, J. V. 
Keywords: Autoregressive Conditional Duration
Issue Date: 2019
Publisher: 0160-7383
Journal: Annals of Tourism Research 
Abstract: Empirically, the length of stay by tourists at their destination usually presents bimodality, overdispersion and non-zero observations, and classical distributions do not seem to fit this type of data very appropriately. In this paper, we introduce two distributions which accommodate bimodality. One is a flexible discrete distribution which can be applied to both bimodal and unimodal data sets. The second distribution is an infinite mixture model that accounts for unobserved heterogeneity in the mean parameter, thus reflecting the heterogeneous preferences of tourists. Both models are suitable for the inclusion of covariates. Our empirical results show that each of these models is suitable and provides a reasonably good fit. Of the two, the infinite mixture model is preferred.
ISSN: 0160-7383
DOI: 10.1016/j.annals.2019.01.006
Source: Annals of Tourism Research[ISSN 0160-7383],v. 75, p. 131-151
Appears in Collections:Artículos
Show full item record

Google ScholarTM




Export metadata

Items in accedaCRIS are protected by copyright, with all rights reserved, unless otherwise indicated.