A question about vectorized operations (avoiding loops, for speed)...
I need to run a simple recursive (autoregressive) filter with a
time-varying coefficient. It is just a one-step recursive filter, so
it would be an exponential decay if the filter was constant.
I just want to do this, where 'x' is the data and 'w' is the
weight to
apply to the previous time step:
x <- c(1, 1, 0, 2, 0, 0)
w <- c(NA, 0.1, 0.5, 0.4, 0.3, 0.2)
y <- x
for (i in seq_along(x)[-1]) y[i] <- y[i] + w[i] * y[i-1]
print(y)
[1] 1.0000 1.1000 0.5500 2.2200 0.6660 0.1332
But, since loops are slow, I would like a vectorized method, like
filter(, method="recursive").
Any ideas?
--
Felix Andrews / ???
PhD candidate, The Fenner School of Environment and Society
The Australian National University (Building 48A), ACT 0200
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