Compute rolling sum by id variables, with missing timepoints

Question

I\'m trying to learn R and there are a few things I\'ve done for 10+ years in SAS that I cannot quite figure out the best way to do in R. Take this data:

 id         


        

Answer 1

A farily efficient answer to this problem could be found using the data.table library.

##Utilize the data.table package
library("data.table")
data <- data.table(t,class,id,count,desired)[order(id,class)]

##Assign each customer an ID
data[,Cust_No:=.GRP,by=c("id","class")]

##Create "list" of comparison dates and values
Ref <- data[,list(Compare_Value=list(I(count)),Compare_Date=list(I(t))), by=c("id","class")]

##Compare two lists and see of the compare date is within N days
data$Roll.Val <- mapply(FUN = function(RD, NUM) {
  d <- as.numeric(Ref$Compare_Date[[NUM]] - RD)
  sum((d <= 0 & d >= -124)*Ref$Compare_Value[[NUM]])
}, RD = data$t,NUM=data$Cust_No)

##Print out data
data <- data[,list(id,class,t,count,desired,Roll.Val)][order(id,class)]
data

id class          t count desired Roll.Val
1:  1     A 2010-01-15     1       1        1
2:  1     A 2010-02-15     2       3        3
3:  1     B 2010-04-15     3       3        3
4:  1     B 2010-09-15     4       4        4
5:  2     A 2010-01-15     5       5        5
6:  2     B 2010-06-15     6       6        6
7:  2     B 2010-08-15     7      13       13
8:  2     B 2010-09-15     8      21       21