bgbb.rf.matrix.LL: BG/BB Log-Likelihood using a recency-frequency matrix
In BTYD: Implementing BTYD Models with the Log Sum Exp Patch

Description Usage Arguments Value References See Also Examples

Calculates the log-likelihood of the BG/BB model.

1	bgbb.rf.matrix.LL(params, rf.matrix)

params

BG/BB parameters - a vector with alpha, beta, gamma, and delta, in that order. Alpha and beta are unobserved parameters for the beta-Bernoulli transaction process. Gamma and delta are unobserved parameters for the beta-geometric dropout process.

rf.matrix

recency-frequency matrix. It must contain columns for frequency ("x"), recency ("t.x"), number of transaction opportunities in the calibration period ("n.cal"), and the number of customers with this combination of recency, frequency and transaction opportunities in the calibration period ("custs"). Note that recency must be the time between the start of the calibration period and the customer's last transaction, not the time between the customer's last transaction and the end of the calibration period.

The total log-likelihood of the provided data in rf.matrix.

Fader, Peter S., Bruce G.S. Hardie, and Jen Shang. "Customer-Base Analysis in a Discrete-Time Noncontractual Setting." Marketing Science 29(6), pp. 1086-1108. 2010. INFORMS. Web.

bgbb.LL

data(donationsSummary)

rf.matrix <- donationsSummary$rf.matrix
# donationsSummary$rf.matrix already has appropriate column names

params <- c(1.20, 0.75, 0.66, 2.78)
bgbb.rf.matrix.LL(params, rf.matrix)