bgnbd.PlotFreqVsConditionalExpectedFrequency: BG/NBD Plot Frequency vs. Conditional Expected Frequency

In BTYD: Implementing BTYD Models with the Log Sum Exp Patch

Description

Plots the actual and conditional expected number transactions made by customers in the holdout period, binned according to calibration period frequencies. Also returns a matrix with this comparison and the number of customers in each bin.

Usage

bgnbd.PlotFreqVsConditionalExpectedFrequency(
  params,
  T.star,
  cal.cbs,
  x.star,
  censor,
  xlab = "Calibration period transactions",
  ylab = "Holdout period transactions",
  xticklab = NULL,
  title = "Conditional Expectation"
)

Arguments

params	BG/NBD parameters - a vector with r, alpha, a, and b, in that order. r and alpha are unobserved parameters for the NBD transaction process. a and b are unobserved parameters for the Beta geometric dropout process.
T.star	length of then holdout period.
cal.cbs	calibration period CBS (customer by sufficient statistic). It must contain columns for frequency ("x"), recency ("t.x"), and total time observed ("T.cal"). Note that recency must be the time between the start of the calibration period and the customer's last transaction, not the time between the customer's last transaction and the end of the calibration period.
x.star	vector of transactions made by each customer in the holdout period.
censor	integer used to censor the data. See details.
xlab	descriptive label for the x axis.
ylab	descriptive label for the y axis.
xticklab	vector containing a label for each tick mark on the x axis.
title	title placed on the top-center of the plot.

Details

This function requires a censor number, which cannot be higher than the highest frequency in the calibration period CBS. The output matrix will have (censor + 1) bins, starting at frequencies of 0 transactions and ending at a bin representing calibration period frequencies at or greater than the censor number.

Value

Holdout period transaction frequency comparison matrix (actual vs. expected).

Examples

data(cdnowSummary)

cal.cbs <- cdnowSummary$cbs
# cal.cbs already has column names required by method

# number of transactions by each customer in the 39 weeks
# following the calibration period
x.star <- cal.cbs[,"x.star"]

# parameters estimated using bgnbd.EstimateParameters
est.params <- c(0.243, 4.414, 0.793, 2.426)
# the maximum censor number that can be used
max(cal.cbs[,"x"])

# plot conditional expected holdout period frequencies,
# binned according to calibration period frequencies
bgnbd.PlotFreqVsConditionalExpectedFrequency(est.params, 
                                             T.star = 39, 
                                             cal.cbs, 
                                             x.star, 
                                             censor = 7)

BTYD documentation built on Nov. 18, 2021, 1:10 a.m.