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32 bgbb.PosteriorMeanTransactionRate<br />
Details<br />
Value<br />
E((P)^l(Theta)^m | alpha, beta, gamma, delta, x, t.x, n)<br />
x, t.x, and n.cal may be vectors. The standard rules for vector operations apply - if they are not<br />
of the same length, shorter vectors will be recycled (start over at the first element) until they are as<br />
long as the longest vector. It is advisable to keep vectors to the same length and to use single values<br />
for parameters that are to be the same for all calculations. If one of these parameters has a length<br />
greater than one, the output will be also be a vector.<br />
The expected posterior (l,m)th product moment.<br />
References<br />
Fader, Peter S., Bruce G.S. Hardie, and Jen Shang. “Customer-Base Analysis in a Discrete-Time<br />
Noncontractual Setting.” Marketing Science 29(6), pp. 1086-1108. 2010. INFORMS. http:<br />
//www.brucehardie.com/papers/020/<br />
See equation 17.<br />
bgbb.PosteriorMeanTransactionRate<br />
BG/BB Posterior Mean Transaction Rate<br />
Description<br />
Usage<br />
Computes the mean value of the marginal posterior value of P, the Bernoulli transaction process<br />
parameter.<br />
bgbb.PosteriorMeanTransactionRate(params, x, t.x, n.cal)<br />
bgbb.rf.matrix.PosteriorMeanTransactionRate(params, rf.matrix)<br />
Arguments<br />
params<br />
x<br />
t.x<br />
n.cal<br />
BG/BB parameters - a vector with alpha, beta, gamma, and delta, in that order.<br />
Alpha and beta are unobserved parameters for the beta-Bernoulli transaction<br />
process. Gamma and delta are unobserved parameters for the beta-geometric<br />
dropout process.<br />
number of repeat transactions a customer made in the calibration period, or a<br />
vector of calibration period transaction frequencies.<br />
recency - the last transaction opportunity in which a customer made a transaction,<br />
or a vector of recencies.<br />
number of transaction opportunities in the calibration period, or a vector of calibration<br />
period transaction opportunities.