Hi Ben and R-help communtiy,
More specifics:
I am using sea-surface temperature (averaged over an area) and also winds
(averaged over an area) to use in a linear regression model as predictors
for rainfall over a small region of Africa. So I have 1 time series of
sea-temp and one timeseries of rainfall (over 36 years - seasonal average)
and I have performed the linear regression between the 2. I now want to
check if the residuals are normally distributed. If they are not I want an
R function that will tell me what distribution they are most similar to -
so that I can apply a suitable transformation to make the data normal.....
Any more tips now that you have a few more details perhaps? :o)
Thanks for your time,
Jenny
On Mon, 30 Jun 2008, Ben Bolker wrote:
Jenny Barnes <jmb <at> mssl.ucl.ac.uk> writes:
Dear R-help community,
Does anybody know of a stats function in R that tells you which
distribution best fits your data? I have tried look through the archives
but have only found functions that tell you if it's normal or log etc.
specifically - I am looking for a function that tells you (given a
timeseries) what the distribution is.
Any help/advice will be greatly appreciated,
All the best,
Jenny Barnes
jmb <at> mssl.ucl.ac.uk
The problem is that it's not generally a good
idea to data-dredge in this way. Your best bet is
to think about the characteristics of the
data (discrete or continuous, non-negative or real,
symmetric or skewed) and try to narrow it down to
a few distributions -- then you can use fitdistr()
(from the MASS package) or something similar
to compare among them.
If you say a little bit more about what
you're trying to do with the data you might
get some more specific advice.
Ben Bolker
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