On 5/31/06, David Hugh-Jones [EMAIL PROTECTED] wrote:
I have a big dataset containing a lot of values for 1970, 1980 and
1990. I want to interpolate values for the years in between, and also
if possible to extrapolate to 1968 and 1969. The method doesn't have
to be clever but I am looking for a function that will do all the data
at once. (Doing foreach, or apply, is just too slow!) Is there
something that will take
list(df$val.1970, df$val.1980, df$val.1990)
as inputs and output an interpolated matrix?
Here are a variety of approaches:
# 1. using lm
y.lm - lm(y ~ tt, list(y = 1:3, tt = seq(1970, 1990, 10)))
predict(y.lm, list(tt = 1968:1990))
# 2. using ts objects:and dyn package
library(dyn)
w - ts(1:3, start = 1970, delta = 10)
w.lm - dyn$lm(w ~ tt, list(tt = time(w)))
predict(w.lm, list(tt = 1968:1990))
# if only interpolation needed using na.approx.zoo
library(zoo)
z - zoo(1:3, c(1970, 1980, 1990))
na.approx(merge(as.zoo(z), zoo(, 1970:1990))) # ignore warning
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