compare-models

R

#Load library and data

library(ChannelAttributionPro)
library(data.table)

Data = read.csv("https://app.channelattribution.io/data/Data.csv",sep=";")

#Set your token

token="yourtoken"

#Compare MTA models

res=compare_models(Data=Data,var_path="path",var_conv="total_conversions",var_null="total_null",
    cha_sep=">",perc_reall=0.1,perc_sample=0.10,max_nsim=10000,min_perc_traffic=0.005,
    niter=10,flg_extra_path=1,max_markov_order=4,seed=1234567,verbose=1)

jpeg("performance_1.jpg")
boxplot(res$performance,main='Simulated Conversion Rate')
dev.off()

#Compare MTA models and Reward model (UAM)

df_paths=fread("https://app.channelattribution.io/data/data_paths_2.csv",sep=";")

df_ctr=fread("https://app.channelattribution.io/data/data_ctr_2.csv",sep=";")

res=compare_models(df_paths=df_paths,df_ctr=df_ctr,channel_conv_name="((CONV))",perc_reall=0.1,perc_sample=0.10,
                   max_nsim=10000,min_perc_traffic=0.005,niter=10,flg_extra_path=1,max_markov_order=4,seed=1234567,
                   verbose=1)

jpeg("performance_2.jpg")
boxplot(res$performance,main='Simulated Conversion Rate')
dev.off()