scoring

14 bgbb.LL
# opportunities.
bgbb.HeatmapHoldoutExpectedTrans(est.params, n.cal=6, n.star=5)
bgbb.LL
BG/BB Log-Likelihood
Description
Calculates the log-likelihood of the BG/BB model.
Usage
bgbb.rf.matrix.LL(params, rf.matrix)
bgbb.LL(params, x, t.x, n.cal)
Arguments
params
rf.matrix
x
t.x
n.cal
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.
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 number of repeat transactions made by the customer in the calibration period.
Can also be vector of frequencies - see details.
recency - the transaction opportunity in which the customer made their last transaction.
Can also be a vector of recencies - see details.
number of transaction opportunities in the calibration period. Can also be a
vector of calibration period transaction opportunities - see details.
Details
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.