auto_markov_model: Automatic Markov Model.

In ChannelAttribution: Markov Model for Online Multi-Channel Attribution

Automatic Markov Model.

Description

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.

Usage

auto_markov_model(Data, var_path, var_conv, var_null, var_value=NULL, 
             max_order=10, roc_npt=100, plot=FALSE, nsim_start=1e5, 
             max_step=NULL, out_more=FALSE, sep=">", 
             ncore=1, nfold=10, seed=0, conv_par=0.05, rate_step_sim=1.5, 
             verbose=TRUE, flg_adv=TRUE)

Arguments

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.
flg_adv	if TRUE, ChannelAttribution Pro banner is printed.

Value

An object of class data.frame with the estimated number of conversions and the estimated conversion value attributed to each channel.

Author(s)

Davide Altomare ([e-mail]).

Examples

## Not run: 

library(ChannelAttribution)

data(PathData) 

auto_markov_model(Data, "path", "total_conversions", "total_null")


## End(Not run)

ChannelAttribution documentation built on May 31, 2023, 9:26 p.m.