Description Usage Arguments Value Author(s) Examples

View source: R/ChannelAttribution.R

Estimate a Markov model from customer journey data after automatically choosing a suitable order. It requires paths that do not lead to conversion as input.

1 2 3 4 5 |

`Data` |
data.frame containing customer journeys data. |

`var_path` |
column name containing paths. |

`var_conv` |
column name containing total conversions. |

`var_null` |
column name containing total paths that do not lead to conversions. |

`var_value` |
column name containing total conversion value. |

`max_order` |
maximum Markov Model order considered. |

`roc_npt` |
number of points used for approximating roc and auc. |

`plot` |
if TRUE, a plot with penalized auc with respect to order will be displayed. |

`nsim_start` |
minimum number of simulations used in computation. |

`max_step` |
maximum number of steps for a single simulated path. if NULL, it is the maximum number of steps found into Data. |

`out_more` |
if TRUE, transition probabilities between channels and removal effects will be shown. |

`sep` |
separator between the channels. |

`ncore` |
number of threads used in computation. |

`nfold` |
how many repetitions are used to verify if convergence is reached at each iteration. |

`seed` |
random seed. Giving this parameter the same value over different runs guarantees that results will not vary. |

`conv_par` |
convergence parameter for the algorithm. The estimation process ends when the percentage of variation of the results over different repetitions is less than convergence parameter. |

`rate_step_sim` |
number of simulations used at each iteration is equal to the number of simulations used at previous iteration multiplied by rate_step_sim. |

`verbose` |
if TRUE, additional information about process convergence will be shown. |

An object of `class`

`data.frame`

with the estimated number of conversions and the estimated conversion value attributed to each channel.

Davide Altomare (info@channelattribution.net).

1 2 3 4 5 6 7 8 9 10 | ```
## Not run:
library(ChannelAttribution)
data(PathData)
auto_markov_model(Data, "path", "total_conversions", "total_null")
## End(Not run)
``` |

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