How to calculate moving average without using filter()?

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 point of apply is to avoid loops, how should I incorporate
this idea into using an apply()?

Construct a vector for grouping and use tapply. Modulo division is a common method for achieving this. Sometimes the seq-function can be used if you adjust the length properly.

tapply(dat, (0:(length(dat)-1))%/%3, mean)

0    1    2    3    4    5    6 
 2.0  5.0  8.0 11.0 14.0 17.0 19.5 


tapply(dat, round(seq(1, (length(dat)/3),  len=length(dat))), mean)
   1    2    3    4    5    6    7 
 1.5  4.5  8.0 11.0 14.5 18.0 20.0 

The comment about weighting dos not seem to be exemplified in your example.

Thanks,
Mike

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