Stratified sampling - not enough observations

Question

What I would like to achieve is get a 10% sample from each group (which is a combination of 2 factors - recency and frequency category). So far I have thought about package

Answer 1

You could always do it yourself:

stratified <- NULL
for(x in 1:6) {
  tmp1 <- sample(rownames(subset(d, r_cat == "A" & f_cat == LETTERS[x])),round(nrow(d[r_cat == "A")*0.1))
  tmp2 <- sample(rownames(subset(d, r_cat == "B" & f_cat == LETTERS[x])),round(nrow(d[r_cat == "B")*0.1))
  tmp3 <- sample(rownames(subset(d, r_cat == "C" & f_cat == LETTERS[x])),round(nrow(d[r_cat == "C")*0.1))
  tmp4 <- sample(rownames(subset(d, r_cat == "D" & f_cat == LETTERS[x])),round(nrow(d[r_cat == "D")*0.1))
  tmp5 <- sample(rownames(subset(d, r_cat == "E" & f_cat == LETTERS[x])),round(nrow(d[r_cat == "E")*0.1))
  tmp6 <- sample(rownames(subset(d, r_cat == "F" & f_cat == LETTERS[x])),round(nrow(d[r_cat == "F")*0.1))
  tmp7 <- sample(rownames(subset(d, r_cat == "G" & f_cat == LETTERS[x])),round(nrow(d[r_cat == "G")*0.1))
  stratified <- c(stratified,tmp1,tmp2,tmp3,tmp4,tmp5,tmp6,tmp7)
}

And then...

d[stratified,] would be your stratified sample.