R dplyr rolling sum

Question

i am implementing a rolling sum calculation through dplyr, but in my database i have a number of variables that have only one or only a few observations, causing an (k is sm

Answer 1

 library(dplyr)
 dg %>% 
   arrange(site,year,animal) %>% 
   group_by(site,animal) %>% 
   mutate(rollsum=cumsum(count))

Answer 2

You can instead use RcppRoll::roll_sum which returns NA if the sample size(n) is less than the window size(k).

set.seed(1)
dg$count = rpois(dim(dg)[1], 5) 
library(RcppRoll)
library(dplyr)
dg %>%
     arrange(site,year,animal) %>%
     group_by(site, animal) %>%
     mutate(roll_sum = roll_sum(count, 2, align = "right", fill = NA))    
#       site year animal count roll_sum
#1    Boston 2000    dog     4       NA
#2    Boston 2001    dog     5        9
#3    Boston 2002    dog     3        8
#4    Boston 2003    dog     9       12
#5    Boston 2004    dog     6       15
#6  New York 2000    dog     4       NA
#7  New York 2001    dog     8       12
#8  New York 2002    dog     8       16
#9  New York 2003    dog     6       14
#10 New York 2004    cat     2       NA

Answer 3

roll_Sum from RcppRoll will return an NA in place of an error wherever the number of data points are the less than the window size.

However, in case you want to return the sum of the number of data points present - even if lesser than the window the size, you can use the rollapplyr function from zoo.

library(zoo)
library(dplyr)

   dg %>%
         arrange(site,year,animal) %>%
         group_by(site, animal) %>%
         mutate(roll_sum = roll_sum(count, 2, align = "right", fill = NA)) %>%
         mutate(rollapply_sum =rollapplyr(count, 2, sum, partial = TRUE) )

Rollapply_sum will return the original value or the sum of data points present, even if its less than the window size instead of returning NA.

       site  year animal count roll_sum rollapply_sum
     (fctr) (int) (fctr) (int)    (dbl)         (int)
1    Boston  2000    dog     4       NA             4
2    Boston  2001    dog     5        9             9
3    Boston  2002    dog     3        8             8
4    Boston  2003    dog     9       12            12
5    Boston  2004    dog     6       15            15
6  New York  2000    dog     4       NA             4
7  New York  2001    dog     8       12            12
8  New York  2002    dog     8       16            16
9  New York  2003    dog     6       14            14
10 New York  2004    cat     2       NA             2