apparelDynCovFuture: Future Time-varying Covariates for the Apparel Retailer...
In CLVTools: Tools for Customer Lifetime Value Estimation
apparelDynCovFuture R Documentation
Future Time-varying Covariates for the Apparel Retailer Dataset
Description
This simulated data contains seasonal information and additional covariates on all 600 customers in the "apparelTrans" after the last transaction in the dataset.
This information can be used as time-varying covariates for prediction future customer behavior.
Usage
data("apparelDynCovFuture")
Format
A data.table with 56,400 rows and 5 variables
- Id
Customer Id
- Cov.Date
Date of contextual factor
- High.Season
Seasonal variable: 1 indicating a time-period that is considered "high season".
- Gender
0=male, 1=female
- Channel
Acquisition channel: 0=online, 1=offline
CLVTools documentation built on Oct. 13, 2024, 9:07 a.m.
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| apparelDynCovFuture | R Documentation |
Future Time-varying Covariates for the Apparel Retailer Dataset
Description
This simulated data contains seasonal information and additional covariates on all 600 customers in the "apparelTrans" after the last transaction in the dataset. This information can be used as time-varying covariates for prediction future customer behavior.
Usage
data("apparelDynCovFuture")
Format
A data.table with 56,400 rows and 5 variables
- Id
Customer Id
- Cov.Date
Date of contextual factor
- High.Season
Seasonal variable: 1 indicating a time-period that is considered "high season".
- Gender
0=male, 1=female
- Channel
Acquisition channel: 0=online, 1=offline
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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