pggg.plotRegularityRateHeterogeneity: Pareto/GGG Plot Regularity Rate Heterogeneity

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

Pareto/GGG Plot Regularity Rate Heterogeneity

Description

Plots and returns the estimated gamma distribution of k (customers' regularity in interpurchase times).

Usage

pggg.plotRegularityRateHeterogeneity(
  draws,
  xmax = NULL,
  fn = NULL,
  title = "Distribution of Regularity Rate k"
)

Arguments

draws	MCMC draws as returned by pggg.mcmc.DrawParameters.
xmax	Upper bound for x-scale.
fn	Optional function to summarize individual-level draws for k, e.g. 'mean'.
title	Plot title.

References

Platzer, M., & Reutterer, T. (2016). Ticking away the moments: Timing regularity helps to better predict customer activity. Marketing Science, 35(5), 779-799. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1287/mksc.2015.0963")}

Examples

data("groceryElog")
cbs <- elog2cbs(groceryElog, T.cal = "2006-12-31")
param.draws <- pggg.mcmc.DrawParameters(cbs,
  mcmc = 20, burnin = 10, thin = 2, chains = 1) # short MCMC to run demo fast
pggg.plotRegularityRateHeterogeneity(param.draws)

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