bgnbd_PAlive | R Documentation |
Calculates the probability of a customer being alive at the end of the calibration period, based on a customer's past transaction behavior and the BG/NBD model parameters.
bgnbd_nocov_PAlive
P(alive) for the BG/NBD model without covariates
bgnbd_staticcov_PAlive
P(alive) for the BG/NBD model with static covariates
bgnbd_nocov_PAlive(r, alpha, a, b, vX, vT_x, vT_cal)
bgnbd_staticcov_PAlive(
r,
alpha,
a,
b,
vX,
vT_x,
vT_cal,
vCovParams_trans,
vCovParams_life,
mCov_trans,
mCov_life
)
r |
shape parameter of the Gamma distribution of the purchase process |
alpha |
scale parameter of the Gamma distribution of the purchase process |
a |
shape parameter of the Beta distribution of the lifetime process |
b |
shape parameter of the Beta distribution of the lifetime process |
vX |
Frequency vector of length n counting the numbers of purchases. |
vT_x |
Recency vector of length n. |
vT_cal |
Vector of length n indicating the total number of periods of observation. |
vCovParams_trans |
Vector of estimated parameters for the transaction covariates. |
vCovParams_life |
Vector of estimated parameters for the lifetime covariates. |
mCov_trans |
Matrix containing the covariates data affecting the transaction process. One column for each covariate. |
mCov_life |
Matrix containing the covariates data affecting the lifetime process. One column for each covariate. |
mCov_trans
is a matrix containing the covariates data of
the time-invariant covariates that affect the transaction process.
Each column represents a different covariate. For every column a gamma parameter
needs to added to vCovParams_trans
at the respective position.
mCov_life
is a matrix containing the covariates data of
the time-invariant covariates that affect the lifetime process.
Each column represents a different covariate. For every column a gamma parameter
needs to added to vCovParams_life
at the respective position.
Returns a vector with the PAlive for each customer.
Fader PS, Hardie BGS, Lee KL (2005). ““Counting Your Customers” the Easy Way: An Alternative to the Pareto/NBD Model” Marketing Science, 24(2), 275-284.
Fader PS, Hardie BGS (2013). “Overcoming the BG/NBD Model's #NUM! Error Problem” URL http://brucehardie.com/notes/027/bgnbd_num_error.pdf.
Fader PS, Hardie BGS (2007). “Incorporating time-invariant covariates into the Pareto/NBD and BG/NBD models.” URL http://www.brucehardie.com/notes/019/time_invariant_covariates.pdf.
Fader PS, Hardie BGS, Lee KL (2007). “Creating a Fit Histogram for the BG/NBD Model” URL https://www.brucehardie.com/notes/014/bgnbd_fit_histogram.pdf
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