Calculates the expected number of transactions in a given time period based on a customer's past transaction behavior and the GGompertz/NBD model parameters.

`ggomnbd_nocov_CET`

Conditional Expected Transactions without covariates`ggomnbd_staticcov_CET`

Conditional Expected Transactions with static covariates

ggomnbd_nocov_CET(r, alpha_0, b, s, beta_0, dPeriods, vX, vT_x, vT_cal) ggomnbd_staticcov_CET( r, alpha_0, b, s, beta_0, dPeriods, vX, vT_x, vT_cal, vCovParams_trans, vCovParams_life, mCov_life, mCov_trans )

r | shape parameter of the Gamma distribution of the purchase process. The smaller r, the stronger the heterogeneity of the purchase process. |
---|---|

alpha_0 | scale parameter of the Gamma distribution of the purchase process. |

b | scale parameter of the Gompertz distribution (constant across customers) |

s | shape parameter of the Gamma distribution for the lifetime process The smaller s, the stronger the heterogeneity of customer lifetimes. |

beta_0 | scale parameter for the Gamma distribution for the lifetime process |

dPeriods | number of periods to predict |

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_life | Matrix containing the covariates data affecting the lifetime process. One column for each covariate. |

mCov_trans | Matrix containing the covariates data affecting the transaction process. One column for each covariate. |

Returns a vector containing the conditional expected transactions for the existing customers in the GGompertz/NBD model.

`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.

Bemmaor AC, Glady N (2012). “Modeling Purchasing Behavior with Sudden “Death”: A Flexible Customer Lifetime Model” Management Science, 58(5), 1012-1021.