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Goodhardt, \u201cA consumer purchasing model with Erlang inter-purchase times,\u201d Journal of the American Statistical Association, vol.68, no.344, pp.828-835, 1973.","DOI":"10.1080\/01621459.1973.10481432"},{"key":"6","doi-asserted-by":"crossref","unstructured":"[6] D.G. Morrison and D.C. Schmittlein, \u201cGeneralizing the NBD model for customer purchases: What are the implications and is it worth the effort?,\u201d Journal of Business & Economic Statistics, vol.6, no.2, pp.145-159, 1988.","DOI":"10.1080\/07350015.1988.10509648"},{"key":"7","doi-asserted-by":"crossref","unstructured":"[7] S. Gupta, \u201cStochastic models of interpurchase time with time-dependent covariates,\u201d Journal of Marketing Research, vol.28, no.1, pp.1-15, 1991.","DOI":"10.2307\/3172722"},{"key":"8","doi-asserted-by":"crossref","unstructured":"[8] G.M. Allenby, R.P. Leone, and L. Jen, \u201cA dynamic model of purchase timing with application to direct marketing,\u201d Journal of the American Statistical Association, vol.94, no.446, pp.365-374, 1999.","DOI":"10.1080\/01621459.1999.10474127"},{"key":"9","doi-asserted-by":"crossref","unstructured":"[9] C.-Y. Huang and C.-S. Lin, \u201cModeling the audience's banner ad exposure for internet advertising planning,\u201d Journal of Advertising, vol.35, no.2, pp.123-136, 2006.","DOI":"10.1080\/00913367.2006.10639236"},{"key":"10","doi-asserted-by":"crossref","unstructured":"[10] K. Kopperschmidt and W. Stute, \u201cPurchase timing models in marketing: A review,\u201d AStA Advances in Statistical Analysis, vol.93, no.2, pp.123-149, 2009.","DOI":"10.1007\/s10182-008-0096-8"},{"key":"11","doi-asserted-by":"crossref","unstructured":"[11] G. Trinh, C. Rungie, M. Wright, C. Driesener, and J. 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Frank, \u201cThe time-rescaling theorem and its application to neural spike train data analysis,\u201d Neural Computation, vol.14, no.2, pp.325-346, 2002.","DOI":"10.1162\/08997660252741149"},{"key":"16","doi-asserted-by":"crossref","unstructured":"[16] Y. Ogata, \u201cStatistical models for earthquake occurrences and residual analysis for point processes,\u201d Journal of the American Statistical Association, vol.83, no.401, pp.9-27, 1988.","DOI":"10.1080\/01621459.1988.10478560"},{"key":"17","doi-asserted-by":"crossref","unstructured":"[17] D.C. Schmittlein, D.G. Morrison, and R. Colombo, \u201cCounting your customers: Who are they and what will they do next?,\u201d Management Science, vol.33, no.1, pp.1-24, 1987.","DOI":"10.1287\/mnsc.33.1.1"},{"key":"18","unstructured":"[18] C. Blundell, K.A. Heller, and J.M. Beck, \u201cModelling reciprocating relationships with hawkes processes,\u201d NIPS, pp.2609-2608, 2012."},{"key":"19","doi-asserted-by":"crossref","unstructured":"[19] A.G. 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