Thanks Jim,
this partially helps (I wasn't aware of the functions you used, which
are good to know).
I have two main doubts about your solution though.
First of all, in my application x is large ~25 elements and I have
to repeat this for ~1000 different y vectors; moreover the range of x
is
If you don't need a 'running average', there are other 'smoothers' you can
look at. Try 'supsmu':
set.seed(1)
x = c(0,1, 3,3.4, 5, 10, 11.23)
y = x**2 + rnorm(length(x))
rbind(x, y)
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
x 0.000 1.00 3.00 3.4
Dear all,
I have a vector x and a vector y = f(x).
e.g.
x = c(0,1, 3,3.4, 5, 10, 11.23)
y = x**2 + rnorm(length(x))
I would like to apply a moving average to y, knowing that the x values
are not uniformly spaced. How can I do this in R?
What alternatives I have to filter out the noise from Y??
Here is one way. I took your data and applied the 'approx' function to get
evenly spaced values and then 'filter' to create a moving average of a
window of size 5.
set.seed(1)
x = c(0,1, 3,3.4, 5, 10, 11.23)
y = x**2 + rnorm(length(x))
rbind(x, y)
# create 'even' spacing using the 'approx'
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