Description Usage Arguments Value References Examples
LCW
is a latent class weibull model implementation based on Fader and Hardie
probability based projection methedology. The survivor function for LCW
is
wS(t|t1,c1)+(1-w)S(t|t2,c2), 0<w<1
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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 |
fitted: |
Fitted Values based on historical data |
projected: |
Projected |
max.likelihood: |
Maximum Likelihood of LCW |
params - t1,t2,c1,c2,w: |
Returns t1,c1,t2,c2,w paramters from maximum likelihood estimation |
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.
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