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30 bgbb.PosteriorMeanDropoutRate
bgbb.PosteriorMeanDropoutRate
BG/BB Posterior Mean Dropout Rate
Description
Usage
Computes the mean value of the marginal posterior value of Theta, the geometric dropout process
parameter.
bgbb.PosteriorMeanDropoutRate(params, x, t.x, n.cal)
bgbb.rf.matrix.PosteriorMeanDropoutRate(params, rf.matrix)
Arguments
params
x
t.x
n.cal
rf.matrix
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.
number of repeat transactions a customer made in the calibration period, or a
vector of calibration period transaction frequencies.
recency - the last transaction opportunity in which a customer made a transaction,
or a vector of recencies.
number of transaction opportunities in the calibration period, or a vector of calibration
period transaction opportunities.
recency-frequency matrix. It must contain columns for frequency ("x"), recency
("t.x"), and the number of transaction opportunities in the calibration period
("n.cal"). 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.
Details
Value
E(Theta | alpha, beta, gamma, delta, x, t.x, n).
bgbb.PosteriorMeanLmProductMoment.
This is calculated by setting l=0 and m=1 in
x, t.x, and n.cal may be vectors. The standard rules for vector operations apply - if they are not
of the same length, shorter vectors will be recycled (start over at the first element) until they are as
long as the longest vector. It is advisable to keep vectors to the same length and to use single values
for parameters that are to be the same for all calculations. If one of these parameters has a length
greater than one, the output will be also be a vector.
The posterior mean dropout rate.