pnbd_DERT {CLVTools} | R Documentation |

Calculates the discounted expected residual transactions.

`pnbd_nocov_DERT`

Discounted expected residual transactions for the Pareto/NBD model without covariates`pnbd_staticcov_DERT`

Discounted expected residual transactions for the Pareto/NBD model with static covariates

pnbd_nocov_DERT( r, alpha_0, s, beta_0, continuous_discount_factor, vX, vT_x, vT_cal ) pnbd_staticcov_DERT( r, alpha_0, s, beta_0, continuous_discount_factor, vX, vT_x, vT_cal, mCov_life, mCov_trans, vCovParams_life, vCovParams_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` |
rate parameter of the Gamma distribution of the purchase process |

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

`beta_0` |
rate parameter for the Gamma distribution for the lifetime process. |

`continuous_discount_factor` |
continuous discount factor to use |

`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. |

`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. |

`vCovParams_life` |
Vector of estimated parameters for the lifetime covariates. |

`vCovParams_trans` |
Vector of estimated parameters for the transaction covariates. |

`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 DERT for each customer.

Schmittlein DC, Morrison DG, Colombo R (1987). “Counting Your Customers: Who-Are They and What Will They Do Next?” Management Science, 33(1), 1-24.

Bachmann P, Meierer M, Naef, J (2021). “The Role of Time-Varying Contextual Factors in Latent Attrition Models for Customer Base Analysis” Marketing Science 40(4). 783-809.

Fader PS, Hardie BGS (2005). “A Note on Deriving the Pareto/NBD Model and Related Expressions.” URL http://www.brucehardie.com/notes/009/pareto_nbd_derivations_2005-11-05.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 (2020). “Deriving an Expression for P(X(t)=x) Under the Pareto/NBD Model.” URL https://www.brucehardie.com/notes/012/pareto_NBD_pmf_derivation_rev.pdf

[Package *CLVTools* version 0.9.0 Index]