mbgcnbd.PlotFreqVsConditionalExpectedFrequency {BTYDplus}

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

Description

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

Usage

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

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

Arguments

params

A vector with model parameters k, r, alpha, a and b, in that order.

T.star

Length of the 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').

x.star

Vector of transactions made by each customer in the holdout period.

censor

Cutoff point for number of transactions in plot.

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

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

See Also

bgcnbd.PlotFreqVsConditionalExpectedFrequency

Examples

## Not run: 
data("groceryElog")
cbs <- elog2cbs(groceryElog, T.cal = "2006-09-30")
params <- mbgcnbd.EstimateParameters(cbs, k=2)
mbgcnbd.PlotFreqVsConditionalExpectedFrequency(params, T.star=52, cbs, cbs$x.star, censor=7)

## End(Not run)