Estimates parameters for the MBG/NBD model via Maximum Likelihood Estimation.
mbgnbd.EstimateParameters(cal.cbs, par.start = c(1, 1, 1, 1),
max.param.value = 10000)calibration period CBS. It must contain columns for frequency
x, for recency t.x and total time observed T.cal. Optionally a
column custs can be provided, which represents number of customers with a
specific combination of frequency x, recency t.x and T.cal.
initial MBG/NBD parameters - a vector with r, alpha,
a and b in that order.
the upper bound on parameters
list of estimated parameters
Batislam, E.P., M. Denizel, A. Filiztekin. 2007. Empirical validation and comparison of models for customer base analysis. International Journal of Research in Marketing 24(3) 201-209. - Hoppe, Daniel, and Udo Wagner. 'Customer base analysis: The case for a central variant of the Betageometric/NBD Model.' Marketing Journal of Research and Management 3.2 (2007): 75-90.