CLVTools v0.11.0

NEW FEATURES

• More memory efficient and faster creation of repeat transactions in clv.data
• Use existing repeat transactions when calling gg with remove.first.transaction = TRUE
• Simplify the formula interfaces latentAttrition() and spending()
• Add predicted.total.spending to predictions
• Harmonize parameter names used in various S3 methods
• Bootstrapping: Add facilities to estimate parameter uncertainty for all models
• Ability to predict future transactions of customers with no existing transaction history
• New start parameters for all latent attrition models
• Pareto/NBD dyncov: Improved numeric stability of PAlive
• GGomNBD: Implement erratum by Jost Adler to predict CET correctly
• GGomNBD: Improve numerical stability and runtime of LL integral
• GGomNBD: Implement PMF as derived by Jost Adler
• lrtest(): Likelihood ratio testing for latent attrition models
• Accept data.table::IDate as data inputs to clvdata
• summary.clv.data:Much faster by improving the calculation of the mean inter-purchase time
• Reduced fitting times for all models by using a compressed CBS as input to the LL sum
• Faster hessian calculation if a model was using correlation

BUG FIXES

• Estimating the Pareto/NBD dyncov with correlation was not possible
• GGomNBD: Free workspace after it is not used anymore to avoid memory-leak
• SetDynamicCovariates: Verify there is no covariate data for nonexistent customers