Compute the maximum value by group and by a time "window"

Question

For the following Panel data (Tracking the Value for unit "ID" over "Time" :

ID=c(1,1,1,1,1,2,2,2,2,2)
Time=c(1,2,3,4,5,1,2,3,4,5)
Value=c(1,9,4,8,5,2,5,9,7,6)

I would like to create a vector which is a maximum value for each "ID" over the last two days (assuming that the unit of Time is a day)

Output vector "Max_Value" would be as follows:

Max_Value=c(1,9,9,8,8,2,5,9,9,7)

To clarify, here's how Max_Value is computed for ID "1".

For ID "1", the maximum value by the "Time=1" is 1, which is a maximum of {1}.

Similarly, for ID "1", the maximum value at the "Time 2" is 9, which is a maximum of {1,9}.

Again, for ID "1", the maximum value at the "Time 3" is 9, which is a maximum of {9,4}.

For ID "1", the maximum value at the "Time 4" is 8, which is a maximum of {4,8}.

For ID "1", the maximum value at the "Time 5" is 8, which is a maximum of {8,5}.

Answer 1

If you just have vectors and Time is complete and sorted, slide + ave could work well for you:

ave(Value, ID, FUN = function(x) slider::slide_dbl(x, max, .before=1))
#> [1] 1 9 9 8 8 2 5 9 9 7

Or even a full Base R solution:

Value[ave(Value, ID, FUN = function(x) c(0, -(diff(x)<0))) + seq_along(Value)]
#> [1] 1 9 9 8 8 2 5 9 9 7

---

Otherwise you can solve it with dplyr + slider:

library(dplyr)
data.frame(ID, Time, Value) %>% 
 group_by(ID) %>% 
 mutate(Max_Value = slider::slide_index_dbl(Value, Time, max, .before=1)) %>% 
 ungroup()

#> # A tibble: 10 x 4
#>       ID  Time Value Max_Value
#>    <dbl> <dbl> <dbl>     <dbl>
#>  1     1     1     1         1
#>  2     1     2     9         9
#>  3     1     3     4         9
#>  4     1     4     8         8
#>  5     1     5     5         8
#>  6     2     1     2         2
#>  7     2     2     5         5
#>  8     2     3     9         9
#>  9     2     4     7         9
#> 10     2     5     6         7