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## Authors: Daniel McCarthy, Lukasz Dziurzynski, Edward Wadsworth
data(cdnowSummary)
## Get the calibration period customer-by-sufficient-statistic matrix from the cdnow data:
cbs <- cdnowSummary$cbs
## Estimate parameters for the BG/NBD model from the CBS:
par.start <- c(1,3,1,3)
params <- bgnbd.EstimateParameters(cbs, par.start)
params
## Check log-likelihood of the params:
bgnbd.cbs.LL(params, cbs)
## Plot the comparison of actual and expected calibration period frequencies:
bgnbd.PlotFrequencyInCalibration(params, cbs, censor=7, plotZero=TRUE)
T.star <- 39 # Length of holdout period
x.star <- cbs[,"x.star"] # Transactions made by each customer in the holdout period
## Plot the comparison of actual and conditional expected holdout period frequencies,
## binned according to calibration period frequencies:
bgnbd.PlotFreqVsConditionalExpectedFrequency(params, T.star, cbs, x.star, censor=7)
## Plot the comparison of actual and conditional expected holdout period frequencies,
## binned according to calibration period recencies:
bgnbd.PlotRecVsConditionalExpectedFrequency(params, cbs, T.star, x.star)
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