Thanks everyone.
For 5 point moving average,
filter(x, side=2, filter=rep(1/5, 5)), versus,
filter(x, side=2, filter=rep(1, 5)
Do they have the same effect, since the total needs to be 1.
Gabor & Rui: I am aware of the zoo package, I did not want to install a
package for one function. Same reas
Hello,
Many packages have a movind average function. For instance package
forecast. Or
library(sos)
findFn("moving average")
In your example, what you compute is not exactly a moving average, but
in can be computed with something like the following.
s <- (seq_along(dat) - 1) %/% 3
sapply(s
On Feb 17, 2014, at 10:45 AM, C W wrote:
> Hi list,
> How do I calculate a moving average without using filter(). filter() does
> not seem to give weighted averages.
>
> I am looking into apply(), tapply,... But nothing "moves".
>
> For example,
>
> dat<-c(1:20)
> mean(dat[1:3])
> mean(dat[4:
There are a zillion answers to this, because your question is really:
How do I smooth a time series? So you can search on appropriate
keywords.
My answer is: don't use moving averages -- that's pathetically
ancient. ?loess is one among the zillions of alternatives you might
consider. Post on CV (s
Hi list,
How do I calculate a moving average without using filter(). filter() does
not seem to give weighted averages.
I am looking into apply(), tapply,... But nothing "moves".
For example,
dat<-c(1:20)
mean(dat[1:3])
mean(dat[4:6])
mean(dat[7:9])
mean(dat[10:12])
etc...
I understand the poi
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