Description Usage Arguments Value References Examples
Uses (M)BG/CNBD-k model parameters to return the probability distribution of purchase frequencies for a random customer in a given time period, i.e. P(X(t)=x|r,alpha,a,b).
1 2 3 | mbgcnbd.pmf(params, t, x)
bgcnbd.pmf(params, t, x)
|
params |
A vector with model parameters |
t |
Length end of time period for which probability is being computed. May also be a vector. |
x |
Number of repeat transactions for which probability is calculated. May also be a vector. |
P(X(t)=x|r,alpha,a,b). If either t
or x
is a
vector, then the output will be a vector as well. If both are vectors, the
output will be a matrix.
(M)BG/CNBD-k: Reutterer, T., Platzer, M., & Schroeder, N. (2020). Leveraging purchase regularity for predicting customer behavior the easy way. International Journal of Research in Marketing. doi: 10.1016/j.ijresmar.2020.09.002
1 2 3 4 5 6 7 8 | ## Not run:
data("groceryElog")
cbs <- elog2cbs(groceryElog)
params <- mbgcnbd.EstimateParameters(cbs)
mbgcnbd.pmf(params, t = 52, x = 0:6)
mbgcnbd.pmf(params, t = c(26, 52), x = 0:6)
## End(Not run)
|
0 1 2 3 4 5 6
0.37402021 0.15535694 0.09439949 0.06625482 0.05002957 0.03943061 0.03194107
26 52
0 0.41709817 0.37402021
1 0.18160807 0.15535694
2 0.10953134 0.09439949
3 0.07397624 0.06625482
4 0.05272559 0.05002957
5 0.03872847 0.03943061
6 0.02898367 0.03194107
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