mcmc.PlotFrequencyInCalibration: Frequency in Calibration Period for Pareto/GGG, Pareto/NBD...

In mplatzer/BTYDplus: Probabilistic Models for Assessing and Predicting your Customer Base

Frequency in Calibration Period for Pareto/GGG, Pareto/NBD (HB) and Pareto/NBD (Abe)

Description

Plots a histogram and returns a matrix comparing the actual and expected number of customers who made a certain number of repeat transactions in the calibration period, binned according to calibration period frequencies.

Usage

mcmc.PlotFrequencyInCalibration(
  draws,
  cal.cbs,
  censor = 7,
  xlab = "Calibration period transactions",
  ylab = "Customers",
  title = "Frequency of Repeat Transactions",
  sample_size = 1000
)

Arguments

draws	MCMC draws as returned by *.mcmc.DrawParameters
cal.cbs	Calibration period customer-by-sufficient-statistic (CBS) data.frame. It must contain columns for frequency ('x') and total time observed ('T.cal').
censor	Cutoff point for number of transactions in plot.
xlab	Descriptive label for the x axis.
ylab	Descriptive label for the y axis.
title	Title placed on the top-center of the plot.
sample_size	Sample size for estimating the probability distribution. See mcmc.pmf.

Details

The method mcmc.pmf is called to calculate the expected numbers based on the corresponding model.

Value

Calibration period repeat transaction frequency comparison matrix (actual vs. expected).

See Also

mcmc.pmf

Examples

## Not run: 
data("groceryElog")
cbs <- elog2cbs(groceryElog, T.cal = "2006-12-31")
param.draws <- pnbd.mcmc.DrawParameters(cbs,
  mcmc = 100, burnin = 50, thin = 10, chains = 1) # short MCMC to run demo fast
mcmc.PlotFrequencyInCalibration(param.draws, cbs, sample_size = 100)

## End(Not run)

mplatzer/BTYDplus documentation built on April 9, 2024, 3:11 a.m.