dc.CreateSpendCBT: Create Spend Customer-by-Time Matrix

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

Description

Creates a customer-by-time matrix with spend per time period.

Usage

dc.CreateSpendCBT(elog, is.avg.spend = FALSE)

Arguments

elog

event log, which is a data frame with columns for customer ID ("cust"), date ("date"), and optionally other columns such as "sales". Each row represents an event, such as a transaction. If the dates are not formatted to be in the order year-month-day, the columns of the customer-by-time matrix may not be ordered chronologically if the "date" column does not consist of date objects (R will order them alphabetically). This will cause problems with other functions, so it is better to convert the date column to date objects before running this function.

is.avg.spend

if TRUE, return average spend customer-by-time matrix; else, return total spend customer-by-time matrix.

Value

Spend customer-by-time matrix.

Examples

# Create event log from file "cdnowElog.csv", which has
# customer IDs in the second column, dates in the third column, and
# sales numbers in the fifth column.
elog <- dc.ReadLines(system.file("data/cdnowElog.csv", package="BTYD"),2,3,5);

# Given that the dates are in the order year-month-day,
# it is not strictly necessary to convert the date column
# to date formats. However, it is good practice:
elog[,"date"] <- as.Date(elog[,"date"], "%Y%m%d")

spend.cbt <- dc.CreateSpendCBT(elog)

Example output

Loading required package: hypergeo
Started reading file. Progress:
1000/6919
2000/6919
3000/6919
4000/6919
5000/6919
6000/6919
File successfully read.
...Completed Spend CBT

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