BdW {foretell} | R Documentation |
Beta discrete Weibull (BdW) Model for Projecting Customer Retention.
Description
BdW
is a beta discrete weibull model implemented based on Fader and Hardie
probability based projection methedology. The survivor function for BdW
is
Beta(a,b+t^c)/Beta(a,b)
Usage
BdW(surv_value, h, lower = c(0.001, 0.001, 0.001), upper = c(10000,
10000, 10000))
Arguments
surv_value |
a numeric vector of historical customer retention percentage should start at 100 and non-starting values should be between 0 and less than 100 |
h |
forecasting horizon |
lower |
lower limit used in |
upper |
upper limit used in |
Value
fitted: |
Fitted values based on historical data |
projected: |
Projected |
max.likelihood: |
Maximum Likelihood of Beta discrete Weibull |
params - a , b and c: |
Returns a and b paramters from maximum likelihood estimation for beta distribution and c |
References
Fader P, Hardie B. How to project customer retention. Journal of Interactive Marketing. 2007;21(1):76-90.
Fader P, Hardie B, Liu Y, Davin J, Steenburgh T. "How to Project Customer Retention" Revisited: The Role of Duration Dependence. Journal of Interactive Marketing. 2018;43:1-16.
Examples
surv_value <- c(100,86.9,74.3,65.3,59.3)
h <- 6
BdW(surv_value,h)