BTYD: Implementing Buy 'Til You Die Models

Description Usage Arguments Details Value References See Also Examples

Plots a heatmap based on the conditional expected holdout period frequency for each recency-frequency combination in the calibration period.

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bgbb.HeatmapHoldoutExpectedTrans(params, n.cal, n.star, xlab = "Recency",
  ylab = "Frequency", xticklab = NULL,
  title = "Heatmap of Conditional Expected Transactions")

`params`	BG/BB parameters - a vector with alpha, beta, gamma, and delta, in that order. Alpha and beta are unobserved parameters for the beta-Bernoulli transaction process. Gamma and delta are unobserved parameters for the beta-geometric dropout process.
`n.cal`	number of transaction opportunities in the calibration period.
`n.star`	number of transaction opportunities in the holdout period.
`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.

E(X(n, n+n*) | alpha, beta, gamma, delta, x, t.x, n). This function requires the holdout period to immediately follow the calibration period.

A matrix containing the conditional expected transactions in the holdout period for each recency-frequency combination in the calibration period. The rows represent calibration period frequencies, and the columns represnt calibration period recencies.

Fader, Peter S., Bruce G.S. Hardie, and Jen Shang. “Customer-Base Analysis in a Discrete-Time Noncontractual Setting.” Marketing Science 29(6), pp. 1086-1108. 2010. INFORMS. http://www.brucehardie.com/papers/020/

bgbb.ConditionalExpectedTransactions

data(donationsSummary)

rf.matrix <- donationsSummary$rf.matrix
# donationsSummary$rf.matrix already has appropriate column names

# starting-point parameters
startingparams <- c(1, 1, 0.5, 3)
# estimated parameters
est.params <- bgbb.EstimateParameters(rf.matrix, startingparams)

# Plot a heatmap of conditional expected transactions in
# a holdout period of 5 transaction opportunities, given
# that the calibration period consisted of 6 transaction
# opportunities.
bgbb.HeatmapHoldoutExpectedTrans(est.params, n.cal=6, n.star=5)