ca_SRM_time_varying {CADF} | R Documentation |
Time varying Simple retention model Estimates retention rate using logistic regression and the simple regression model Mostly used for contractual models where there are clear opportunities for cancellation. Could be used in non-contractional situations although the cancellation opportunities should be defined. Not recommended for use with services that consumers use rotating-door style. Use the migration model there.
Description
Time varying Simple retention model Estimates retention rate using logistic regression and the simple regression model Mostly used for contractual models where there are clear opportunities for cancellation. Could be used in non-contractional situations although the cancellation opportunities should be defined. Not recommended for use with services that consumers use rotating-door style. Use the migration model there.
Usage
ca_SRM_time_varying(df_logistic, reference_level = 12, maxT = 12)
Arguments
df_logistic |
A data frame, formatted for logistic regression. 1 row for each customer id/timeperiod. 1/0 for purchase. |
reference_level |
All coefficients will be judged relevant to the reference level. It defaults to time period 12. (Note interpretation will change based on how T is formulated.) |
maxT |
The number of timeperiods to build. |
Value
Returns logistic model results (the glm model)
Examples
library(stats)
x <- c(3, 1, 5)
df_logistic <- bigT_expand_via_apply(x)
model <- ca_SRM_time_varying(df_logistic, reference_level = 3)