Compares the density of the observed average spending per transaction (empirical distribution) to the model's distribution of mean transaction spending (weighted by the actual number of transactions).
# S3 method for clv.fitted.spending plot(x, n = 256, verbose = TRUE, ...) # S4 method for clv.fitted.spending plot(x, n = 256, verbose = TRUE, ...)
The fitted spending model to plot
Number of points at which the empirical and model density are calculated. Should be a power of two.
Show details about the running of the function.
An object of class
ggplot from package
ggplot2 is returned by default.
Colombo R, Jiang W (1999). “A stochastic RFM model.” Journal of Interactive Marketing, 13(3), 2–12.
Fader PS, Hardie BG, Lee K (2005). “RFM and CLV: Using Iso-Value Curves for Customer Base Analysis.” Journal of Marketing Research, 42(4), 415–430.
Fader PS, Hardie BG (2013). “The Gamma-Gamma Model of Monetary Value.” URL http://www.brucehardie.com/notes/025/gamma_gamma.pdf.
plot for transaction models