mbgcnbd.PlotRecVsConditionalExpectedFrequency: (M)BG/CNBD-k Plot Actual vs. Conditional Expected Frequency...

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

(M)BG/CNBD-k Plot Actual vs. Conditional Expected Frequency by Recency

Description

Plots the actual and conditional expected number transactions made by customers in the holdout period, binned according to calibration period recencies, and returns this comparison in a matrix.

Usage

mbgcnbd.PlotRecVsConditionalExpectedFrequency(
  params,
  cal.cbs,
  T.star,
  x.star,
  xlab = "Calibration period recency",
  ylab = "Holdout period transactions",
  xticklab = NULL,
  title = "Actual vs. Conditional Expected Transactions by Recency"
)

bgcnbd.PlotRecVsConditionalExpectedFrequency(
  params,
  cal.cbs,
  T.star,
  x.star,
  xlab = "Calibration period recency",
  ylab = "Holdout period transactions",
  xticklab = NULL,
  title = "Actual vs. Conditional Expected Transactions by Recency"
)

Arguments

params	A vector with model parameters k, r, alpha, a and b, in that order.
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').
T.star	Length of the holdout period.
x.star	Vector of transactions made by each customer in the holdout period.
xlab	Descriptive label for the x axis.
ylab	Descriptive label for the x axis.
xticklab	A vector containing a label for each tick mark on the x axis.
title	Title placed on the top-center of the plot.

Value

Matrix comparing actual and conditional expected transactions in the holdout period.

See Also

bgcnbd.PlotFreqVsConditionalExpectedFrequency

Examples

## Not run: 
data("groceryElog")
cbs <- elog2cbs(groceryElog, T.cal = "2006-09-30")
params <- mbgcnbd.EstimateParameters(cbs, k=2)
mbgcnbd.PlotRecVsConditionalExpectedFrequency(params, cbs, T.star=52, cbs$x.star)

## End(Not run)

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