- add implementation of BG/CNBD-k model - (m)bgcnbd.ConditionalExpectedTransactions uses original approximation again - mbgcnbd.ConditionalExpectedTransactions can now handle customers with many (170+) transactions; thanks to Andrea Rumenjak for providing the patch;
0.5.0
- rename model from CBG/CNBD to MBG/CNBD - function prefixes changed from cbgcnbd to mbgcnbd accordingly - improve approximation logic for mbgcnbd.ConditionalExpectedTransactions
0.4.0
- rename model from Pareto/CNBD to Pareto/GGG - function prefixes changed from pcnbd to pggg accordingly - cust-column is assigned as names to list of level_1 CODA-objects returned by MCMC drawParameter methods - this makes it easier to access these via customer ID - rename to cbgcnbd.EstimateRegularity() to estimateRegularity(), because the method is not bound to CBG/CNBD-k model - add tests and demo
0.3.3
- add mc.cores parameter to MCMC methods to explicitely set number of parallel cores to be used - important bug-fix for pcnbd.mcmc.DrawParameters - draw_tau slice-samples now from correct log_posterior in churn case - more realistic test case for P/NBD MCMC, plus minor change to handling numeric underflow resulting in more accurate parameter estimates - pcnbd.GenerateData now correctly considers fixed parameter value for k - pcnbd.GenerateData has minimum level of 0.1 for generated k's in order to avoid itt's if 0