dc.MergeCustomers {BTYD}

Merge Customers

Description

Takes two CBT or CBS matrices and ensures that the second one has the same row names as the first.

Usage

dc.MergeCustomers(data.correct, data.to.correct)

Arguments

data.correct

CBT or CBS with the correct customer IDs as row names. Usually from the calibration period.

data.to.correct

CBT or CBS which needs to be fixed (customer IDs inserted). Usually from the holdout period.

Details

Care should be taken in using this function. It inserts zero values in all rows that were not in the original holdout period data. This behavior does not cause a problem if using CBT matrices, but will cause a problem if using CBS matrices (for example, the output will report all customers with a holdout period length of zero). However, this particular issue is easily fixed (see examples) and should not cause problems.

A work-around to avoid using this function is presented in the example for dc.BuildCBSFromCBTAndDates - build the full CBT and only use the columns applying to each particular time period to construct separate CBTs, and from them, CBSs. That is a much cleaner and less error-prone method; however, on occasion the data will not be available in event log format and you may not be able to construct a CBT for both time periods together.

Value

Updated holdout period CBT or CBS.

Examples

elog <- dc.ReadLines(system.file("data/cdnowElog.csv", package="BTYD"),2,3,5)
elog[,"date"] <- as.Date(elog[,"date"], "%Y%m%d")
cutoff.date <- as.Date("1997-09-30")
cal.elog <- elog[which(elog[,"date"] <= cutoff.date),]
holdout.elog <- elog[which(elog[,"date"] > cutoff.date),]

# Create calibration period CBT from cal.elog
cal.reach.cbt <- dc.CreateReachCBT(cal.elog)
# Create holdout period CBT from holdout.elog
holdout.reach.cbt <- dc.CreateReachCBT(holdout.elog)

# Note the difference:
nrow(cal.reach.cbt)            # 2357 customers
nrow(holdout.reach.cbt)        # 684 customers

# Create a "fixed" holdout period CBT, with the same number
# of customers in the same order as the calibration period CBT
fixed.holdout.reach.cbt <- dc.MergeCustomers(cal.reach.cbt, holdout.reach.cbt)
nrow(fixed.holdout.reach.cbt)  # 2357 customers

# You can verify that the above is correct by turning these into a CBS
# (see \code{\link{dc.BuildCBSFromCBTAndDates}} and using
# \code{\link{pnbd.PlotFreqVsConditionalExpectedFrequency}}, for example

# Alternatively, we can fix the CBS, instead of the CBS:

cal.start.dates.indices <- dc.GetFirstPurchasePeriodsFromCBT(cal.reach.cbt)
cal.start.dates <- as.Date(colnames(cal.reach.cbt)[cal.start.dates.indices])
cal.end.dates.indices <- dc.GetLastPurchasePeriodsFromCBT(cal.reach.cbt)
cal.end.dates <- as.Date(colnames(cal.reach.cbt)[cal.end.dates.indices])
T.cal.total <- rep(cutoff.date, nrow(cal.reach.cbt))
cal.dates <- data.frame(cal.start.dates, cal.end.dates, T.cal.total)

# Create calibration period customer-by-sufficient-statistic data frame,
# using weeks as the unit of time.
cal.cbs <- dc.BuildCBSFromCBTAndDates(cal.reach.cbt,
                                      cal.dates,
                                      per="week",
                                      cbt.is.during.cal.period=TRUE)

# Force the calibration period customer-by-sufficient-statistic to only
# 	contain repeat transactions (required by BG/BB and Pareto/NBD models)
cal.cbs[,"x"] <- cal.cbs[,"x"] - 1

holdout.start <- cutoff.date+1
holdout.end <- as.Date(colnames(fixed.holdout.reach.cbt)[ncol(fixed.holdout.reach.cbt)])
holdout.dates <- c(holdout.start, holdout.end)

# Create holdout period customer-by-sufficient-statistic data frame,
# using weeks as the unit of time.
holdout.cbs <- dc.BuildCBSFromCBTAndDates(holdout.reach.cbt,
                                          holdout.dates,
                                          per="week",
                                          cbt.is.during.cal.period=FALSE)

# Note the difference:
nrow(cal.cbs)            # 2357 customers
nrow(holdout.cbs)        # 684 customers

# Create a "fixed" holdout period CBS, with the same number
# of customers in the same order as the calibration period CBS
fixed.holdout.cbs <- dc.MergeCustomers(cal.cbs, holdout.cbs)
nrow(fixed.holdout.cbs)  # 2357 customers

# Furthermore, this function will assign a zero value to all fields
# that were not in the original holdout period CBS. Since T.star is the
# same for all customers in the holdout period, we should fix that:
fixed.holdout.cbs[,"T.star"] <- rep(max(fixed.holdout.cbs[,"T.star"]),nrow(fixed.holdout.cbs))