Hi! I’m attempting to use Rscript to do some automated plotting. It is
working well, except that I seem to be running into a maximum line length
issue, and I’m wondering if it is a bug on your end. Here’s an example of the
command I’m trying to run:
/usr/local/bin/Rscript -e '{x <- c(-1.31
> /Henrik
>
> On Fri, Apr 21, 2017 at 11:07 AM, Ben Tupper wrote:
>> Hi,
>>
>> I suspect you are over the 10kb limit for the expression. See
>>
>> https://cran.r-project.org/doc/manuals/r-release/R-intro.html#Invoking-R-from-the-command-line
>>
>
eems to be quite uncommon, so I've had
trouble finding out how others have dealt with these sorts of issues that crop
up only with higher powers.
Ben Haller
McGill University
http://biology.mcgill.ca/grad/ben/
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R-help@r-project.org mailing list
ht
;
> x_qt <- x^4 # shorter code-wise
> and you can certain just enter a quartic term if the data is just
> quartic and you are not really itnerested in the lower trends.
Yep, for sure.
Thanks!
Ben Haller
McGill University
http://biology.mcgill.ca/grad/ben/
___
On May 6, 2011, at 12:31 PM, David Winsemius wrote:
> On May 6, 2011, at 11:35 AM, Ben Haller wrote:
>
>> Hi all! I'm getting a model fit from glm() (a binary logistic regression
>> fit, but I don't think that's important) for a formula that contains powers
em easy to post an example, since my dataset is so large, but if
either of you would be willing to look at this further, I could upload my
dataset to a web server somewhere and post a link to it. In any case, thanks
very much for your help; I'll look into the things you mentioned.
Ben Halle
On May 6, 2011, at 4:27 PM, David Winsemius wrote:
> On May 6, 2011, at 4:16 PM, Ben Haller wrote:
>>
>
>> As for correlated coefficients: x, x^2, x^3 etc. would obviously be highly
>> correlated, for values close to zero.
>
> Not just for x close to zero:
&g
ry small coefficients? Or should I use the lasso, and
just ignore, in my explanation of the model, terms with tiny coefficients? Or
is there some other way of handling this problem?
Thanks to anybody who has even read this far, and many many thanks to any
responses!
Ben Haller
McGill University
te(slope, curvature) + te(slope, amplitude) + te(curvature,
amplitude) + te(acl, dispersal) + te(amplitude, dispersal) + te(slope,
curvature, amplitude), family=binomial, data=rla, method="REML")
So. Any advice? How can I correctly do a gam() fit involving multiple
inte
think of ANOVA as involving discrete levels
(factors) in the independent variables, like treatment groups. My independent
variables are all continuous, so I would not have thought of this as ANOVA.
Anyhow, OK. I will go get that book today, and see if I can figure all this
out.
Thanks for
arched Google and the R lists for information about this error,
and while I did find a couple of other people asking about it, I didn't find
any advice about what to do about it that I can apply to my situation.
I'd be happy to share my dataset with anyone willing to help me on this,
r the package (MASS) that defines polr(), but haven't
discovered anything.
Thanks!
Ben Haller
McGill University
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PLEASE do read the posting guide http://www.R-proj
On Feb 17, 2011, at 11:40 AM, Alaios wrote:
> ...Is it possible to split work in many cores in R and if yes how is this
> library called?
I'd recommend the "mclapply" function in the "multicore" package. The only
drawback is that you can't run your code i
quite nicely. Just in case
anybody cares. :->
Ben Haller
McGill University
On Feb 16, 2011, at 5:41 PM, Ben Haller wrote:
> Hi all. I'm just starting to explore ordinal multinomial regression. My
> dataset is 300,000 rows, with an outcome (ordinal factor from 1 to 9) and
always interested in learning how to do
things better.
And of course this code is provided without warranty, may have bugs, etc.
Enjoy!
Ben Haller
McGill University
correlation_stats <- function(p, n_pairs=20)
{
# Compute Moran's I and Geary's C for the landscape p. T
looking at only points within a smaller window risks getting a
value that is not representative of the larger context. But if it makes sense
to you in your application, then more power to you. :->
Ben Haller
McGill University
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R-help@r-project
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