$leak_num[ix] <- rep(v[r$values], r$lengths[r$values])
> d
>
>
> Hope this helps,
>
> Rui Barradas
>
> Em 24-05-2012 11:00, Max Brondfield escreveu:
>
>> Date: Wed, 23 May 2012 16:42:02 -0400
>> From: Max Brondfield
>> >
>> To:r-help@r-proj
Hi all,
I am working with a spatial data set for which I am only interested in high
concentration values ("leaks"). The low values (< 90th percentile) have
already been turned into NA's, leaving me with a matrix like this:
< CH4_leak
lonlatCH4
1 -71.11954 42.35068 2
Dear all,
I am trying to analyze some non-linear data to which I have fit a curve of
the following form:
dum <- nls(y~(A + (B*x)/(C+x)), start = list(A=370,B=100,C=23000))
I am wondering if there is any way to determine meaningful quality of fit
statistics from the nls function?
A summary yields
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