Hello
Lets say as an example I have a dataframe with the following attributes:
rownum(1:405), colnum(1:287), year(2000:2009), daily(rownum x colnum x year)
and foragePotential (0:1, by 0.01). The data is actually stored in a netcdf
file and I'm trying to provide a conceptual version of the data.
Ok. I need to calculate a moving mean and a moving variance for each cell on
the following temporal
windows - 7 day, 14 day, and 28 day. So far I have code for the moving
average.
ma <- function(x , n) {
filter(x, rep(1/n, n), sides = 1)
} # note that when the function is used, n is defined for the
temporal period (7, 14, and 28), and x is the input variable.
ma7 <- ma(dat, 7) # where dat is accessing the foraging potential of the
birds.
ma14 <- ma(dat, 14)
ma28 <- ma(dat, 28)
This works fine. What I don't have is the code for a moving variance.
filter in the function above is included in the stats package and conducts a
linear filtering on a Time Series.
Is there comparable code some place in R for a moving variance?
Thanks in advance.
Thanks,
Steve
[[alternative HTML version deleted]]