> On Nov 15, 2014, at 7:19 AM, Aravindhan, K wrote:
>
> Hi David,
> I am using generalized linear models (glm command with family="poisson").
You still have not answered what sort of pseudo-R^2 measure you expected.
http://www.econ.ucdavis.edu/faculty/cameron/research/jbes96preprint.pdf
—
D
Hi William,
Thank you very much for your reply.
I did a subsampling to reduce the number of samples to ~1.8 million. It
seems to work fine except for 99th percentile (p-values for all the
features are 1.0). Does this mean I’m subsampling too much? How should I
interpret the result?
tau: [1] 0.25
You can time it yourself on increasingly large subsets of your data. E.g.,
> dat <- data.frame(x1=rnorm(1e6), x2=rnorm(1e6),
x3=sample(c("A","B","C"),size=1e6,replace=TRUE))
> dat$y <- with(dat, x1 + 2*(x3=="B")*x2 + rnorm(1e6))
> t <- vapply(n<-4^(3:10),FUN=function(n){d<-dat[seq_len(n),];
print
Hi all,
I'm using quantreg rq() to perform quantile regression on a large data set.
Each record has 4 fields and there are about 18 million records in total. I
wonder if anyone has tried rq() on a large dataset and how long I should
expect it to finish. Or it is simply too large and I should subsa
Greetings. I'd like to get some advice about using OpenBLAS with R, rather
than using the BLAS that comes built in to R.
I've tried this on my Fedora 20 system (see the appended for details). I ran
a simple test -- multiplying two large matrices -- and the results were very
impressive, i.e., in
The data you are working with us at least as important as the algorithms you
work with. You need to learn what information to give us in order for our
response to help you. You can start by reading the Posting Guide mentioned in
the footer of any message on this list. One important item mentione
If you go to:
https://stat.ethz.ch/mailman/listinfo/r-help
as given in the footer of all list messages, the only thing you
require to unsubscribe is the email address you used to subscribe to
the list, which you obviously know since you sent this message from
it.
Sarah
On Sat, Nov 15, 2014 at 3:0
I do not have my login information anymore but I do not want to receive any
R help emails again.
Thank you.
[[alternative HTML version deleted]]
__
R-help@r-project.org mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read th
Please read the Posting Guide... this question is too vague.
a) There are plenty of online references as to how to use R to fit various
kinds of models. If you understand which algorithms you want to use, you should
be able to find an example or even just a relevant R package using appropriate
On 15/11/2014, 11:26 AM, Jeff Newmiller wrote:
> AFAIK You have to alter the name of at least one of the y arguments as used
> by foobar, and anyone calling foobar has to read about that in the help file.
> That is only one y can be in "...". e.g.
>
> foobar <- function( x, y_foo, ... ) {
> fo
On Nov 14, 2014, at 3:18 PM, David Winsemius wrote:
>
> On Nov 14, 2014, at 12:15 PM, ivan wrote:
>
>> Hi,
>>
>> I am trying to compute bootstrap confidence intervals for weighted means of
>> paired differences with the boot package. Unfortunately, the weighted mean
>> estimate lies out of the
AFAIK You have to alter the name of at least one of the y arguments as used by
foobar, and anyone calling foobar has to read about that in the help file. That
is only one y can be in "...". e.g.
foobar <- function( x, y_foo, ... ) {
foo( x, y=y_foo, ... )
bar( x, ... )
}
--
I have to fit a model to growth data of Hevea (rubber) trees. The details
are outlined in the attached docx file. Kind help is solicited.
--
Dr. TR Chandrasekhar, M.Sc., M. Tech., Ph. D.,
Sr. Scientist
Rubber Research Institute of India
Hevea Breeding Sub Station
Kadaba - 574 221
DK Dt., Karnatak
Respected sir i am a student of Mphil statistics from pakistan, please i have a
great problem and i try my best but can not solve, sir the problem is that i
want to estimate the parameters of LN3 for a set of data having name x
by MLE method, in R, i also apply the VGAM package but c
Hi David,
I am using generalized linear models (glm command with family="poisson").
Thanks
Aravindhan
-Original Message-
From: David Winsemius [mailto:dwinsem...@comcast.net]
Sent: Saturday, November 15, 2014 1:16 PM
To: Aravindhan, K
Cc: R-help@r-project.org
Subject: Re: [R] how to com
Dear list,
I wonder if there's a clever way to fine control the exact way arguments
are dispatched via R's "three dots" argument
Consider the following use case:
- you have a function foobar() that calls foo() which in turn calls bar()
- *both* foo() and bar() have an argument that's
Ok, I have to admit: that was a really stupid mistake :-/
I unintentionally had a trailing `,` in the call to `nestr::setNested()`
inside `optionr::setAnywhereOption()`
Here's a much simpler illustration:
*Definitions* //
setGeneric(
name = "setAnywhereOption",
signature = "id",
Preetam,
You are more likely to want garch than
arch.
These models are data-hungry, so I'm
sceptical that a model with CPI is going
to be very good. See for instance:
www.portfolioprobe.com/2012/09/20/garch-estimation-on-impossibly-long-series/
This question is really more appropriate
for r-s
Hi,
I have two variables, FTSE100 and CPI . Call them Y and X respectively.
I want to fit an ARCH(1) to model Y on X. I also intend to predict the
values of Y for future (given) values of X. How can I use R for such
prediction?
Another question is: is there a way I can call an R function which wo
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