need help with data management

On Sat, Dec 25, 2010 at 8:08 AM, analyst41 at hotmail.com

I have a data frame that reads

client ID date transcations

323232 ? 11/1/2010 22
323232 ? 11/2/2010 0
323232 ? 11/3/2010 missing
121212 ? 11/10/2010 32
121212 ? ?11/11/2010 15
.................................


I want to order the rows by client ID and date and using a black-box
forecasting method create the data fcst(client,date of forecast, date
for which forecast applies).

?Assume that I have a function that given a time series
x(1),x(2),....x(k) will generate f(i,j) where f(i,j) = forecast j days
ahead, given data till date i.

How can the forecast data be best stored and how would I go about the
taks of processing all the clients and dates?

This isn't quite what you asked but it seems more suitable to what you
need.  Instead of using long form data we transform it to wide form
with one client per column.  Try copying this from this post and
pasting it into your R session:

Lines <- "323232   11/1/2010 22
323232   11/2/2010 0
323232   11/3/2010 missing
121212   11/10/2010 32
121212    11/11/2010 15"

library(zoo)
library(chron)

# read in. split = 1 converts to wide form
# can use "myfile.dat" in place of textConnection(Lines) for real data
z <- read.zoo(textConnection(Lines), split = 1, index = 2, FUN = chron,
      na.strings = "missing")
# d is matrix with one row per date and one col per client
d <- coredata(z)

# just use last point as our forecast for next 3 dates
naive.forecast <- function(x) rep(tail(x, 1), 3)
pred <- apply(d, 2, naive.forecast)

# put predictions together with the data
rbind(d, pred)


For the data you showed this gives:

rbind(d, pred)

121212 323232
[1,]     NA     22
[2,]     NA      0
[3,]     NA     NA
[4,]     32     NA
[5,]     15     NA
[6,]     15     NA
[7,]     15     NA
[8,]     15     NA

Statistics & Software Consulting
GKX Group, GKX Associates Inc.
tel: 1-877-GKX-GROUP
email: ggrothendieck at gmail.com