bgnbd.Expectation: BG/NBD Expectation
In BTYD: Implementing BTYD Models with the Log Sum Exp Patch

Description Usage Arguments Details Value References See Also Examples

Returns the number of repeat transactions that a randomly chosen customer (for whom we have no prior information) is expected to make in a given time period.

1	bgnbd.Expectation(params, t, hardie = TRUE)

`params`	BG/NBD parameters - a vector with r, alpha, a, and b, in that order. r and alpha are unobserved parameters for the NBD transaction process. a and b are unobserved parameters for the Beta geometric dropout process.
`t`	length of time for which we are calculating the expected number of repeat transactions.
`hardie`	if TRUE, use `h2f1` instead of `hypergeo`.

E(X(t) | r, alpha, a, b)

Number of repeat transactions a customer is expected to make in a time period of length t.

Fader, Peter S.; Hardie, Bruce G.S.and Lee, Ka Lok. “Computing P(alive) Using the BG/NBD Model.” December. 2008. Web. http://www.brucehardie.com/notes/021/palive_for_BGNBD.pdf

bgnbd.ConditionalExpectedTransactions

params <- c(0.243, 4.414, 0.793, 2.426)

# Number of repeat transactions a customer is expected to make in 2 time intervals.
bgnbd.Expectation(params, t=2, hardie = FALSE)

# We can also compare expected transactions over time:
bgnbd.Expectation(params, t=1:10)