Unexpected NA values when calculating rolling mean with `zoo` on time series in R
I'm migrating some code and I'm working with an scenario when trying to compute a rolling mean on a time series dataset using the `zoo` package in R. My dataset has some missing values, and I want to maintain the time series structure while applying the rolling mean, but it seems to introduce NA values unexpectedly. Here’s a simplified version of my code: ```r library(zoo) # Creating a time series dataset with NA values set.seed(123) data <- data.frame( date = seq(as.Date('2023-01-01'), by = 'day', length.out = 10), value = c(1, 2, NA, 4, 5, NA, NA, 8, 9, 10) ) # Applying the rollmean function from `zoo` rolling_mean <- rollmean(data$value, k = 3, fill = NA, align = 'right') ``` When I execute this code, I expect the rolling mean to handle the NA values gracefully, but instead, I get an output where more NA values are introduced than I anticipated. The resulting vector looks like this: ```r [1] NA 2.0 3.0 4.0 5.0 NA NA 8.0 9.0 10.0 ``` I assumed that specifying `fill = NA` would keep the structure intact without introducing additional NAs, but it seems that the window function doesn’t handle the NA values as I expected. I tried using different values for the `fill` parameter and even added the `na.rm = TRUE` argument inside the `rollmean`, but it didn't give me the desired result. If anyone has insights on how to compute a rolling mean while effectively managing NA values in the input time series, I would greatly appreciate your help. I'm using R version 4.1.1 and `zoo` version 1.8-9.