Dear Harsh:
I stole these lines from the Persp examples and
the plotmath examples.
x - seq(-10, 10, length= 30)
y - x
f - function(x,y) { r - sqrt(x^2+y^2); 10 * sin(r)/r }
z - outer(x, y, f)
z[is.na(z)] - 1
op - par(bg = white)
persp(x, y, z, theta =
?regex does describe this:
A range of characters may be specified by giving the first and last
characters, separated by a hyphen. (Character ranges are
interpreted in the collation order of the current locale.)
You did not tell us your locale, but based on questions from you
Hi,
I want to use Maximum likelihood to estimate the parameters from my regression
line.
I have purchased the book Applied linear statistical models from Neter,
Kutner, nachtsheim Wasserman, and in one of the first chapters, they use
maximum likelihood to estimate the parameters.
Now I want
mle(stats4)Maximum Likelihood Estimation
is it list above what you want?
On 6/10/06, Bart Joosen [EMAIL PROTECTED] wrote:
Hi,
I want to use Maximum likelihood to estimate the parameters from my regression
line.
I have purchased the book Applied linear statistical models from
I get the same result in a US collate ordering:
strsplit(Sys.getlocale(), ;)
[[1]]
[1] LC_COLLATE=English_United States.1252
[2] LC_CTYPE=English_United States.1252
[3] LC_MONETARY=English_United States.1252
[4] LC_NUMERIC=C
[5] LC_TIME=English_United States.1252
grep([W-Z], letters, value =
John,
The advice in the posting guide:
--
Do your homework before posting: [...]
* Do help.search(keyword) with different keywords (type this at the R
prompt)
--
seems to work.
Using
help.search(mod)
follow the first hit:
?+
Chuck
On Fri, 9 Jun 2006, Kerpel, John
Dear R-Help,
As with the rpois() function to generate random data for a poisson
distribution, I need to generate random data for a quasi distribution with
var=mu^2.
Does anyone known how to do this?
Thanks in advance,
Hugues SANTIN-JANIN.
[[alternative HTML version deleted]]
On Thu, Jun 08, 2006 at 08:31:26PM +0200, Pedro Ramirez wrote:
In mathematical terms the optimal bandwith for density estimation
decreases at rate n^{-1/5}, while the one for distribution function
decreases at rate n^{-1/3}, if n is the sample size. In practical terms,
one must choose an
I have seen no reply to this, so I will offer a couple of comments in
spite of the fact that I know very little about aov other than it is
old and has largely been superceded by lme in the nlme package.
I've replied to many posts on random and mixed effects over the past few
years,
Hi,
I'm Sorry for any cross-posting. I've reviewed the archives and could
not find an exact answer to my question below.
I'm trying to generate very large sparse matrices ( 1% non-zero
entries per row). I have a sparse matrix function below which works
well until the row/col count exceeds
You need to look at the packages specifically designed for
sparse matrices: SparseM and Matrix.
url:www.econ.uiuc.edu/~rogerRoger Koenker
email [EMAIL PROTECTED] Department of Economics
vox:217-333-4558University of
see inline
Eric Pante wrote:
Hi Spencer,
First, thank you very much for taking the time to write this detailed
reply !
I did try exactly the formula you suggested:
fit - lme(fixed=COVER ~ HABITAT, random = ~1|LAGOON/HABITAT,
data=cov)
before writing my post, and
Hello,
Is there any software project that uses R to do log file analisys?
thanks
gabi
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PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
Hello friends and fellow R users,
I have successfully tabulated and entered my survival data into R and
have generated survival curves. But I would like to be able to determine
what the survival rates are now at one month, three months, six months
and one year.
I have a data set, via.wall, which
Any quasi distribution is not well defined, which is why it is
called qausi. Users decide that its likelihood looks like some
other distribution, e.g. a Poisson, but it is overdispersed.
If you want to simulate a quasi binomial, you have to select a
plausible
On Sat, 10 Jun 2006, g l wrote:
Hi,
I'm Sorry for any cross-posting. I've reviewed the archives and could
not find an exact answer to my question below.
I'm trying to generate very large sparse matrices ( 1% non-zero
entries per row). I have a sparse matrix function below which works
well
As an example of how one might do this sort of thing in SparseM
ignoring the rounding aspect...
require(SparseM)
require(msm) #for rtnorm
sm - function(dim,rnd,q){
n - rbinom(1, dim * dim, 2 * pnorm(q) - 1)
ia - sample(dim,n,replace = TRUE)
ja - sample(dim,n,replace =
Evidently, your 'trimmed_dates' was NOT a a Julian date value, as
returned by 'mdy.date()', number of days since 1/1/1960.
My standard references for this kind of thing are the zoo vignette
and the R News article, Gabor Grothendieck and Thomas Petzoldt. R help
desk:
Have you tried Bioconductor (www.bioconductor.org)? I haven't seen
any replies to your question, and I know next to nothing about
microarray data. I understand that Bioconductor specializes in
microarray and related data, has a listserve, etc.
hope this helps,
Dear R-friends
I have a table with more than 50 columns (variables). Many of them are
numeric and others are of type char. I would like repeat a group of command
using only a set of the numeric variables, excluding others (for example V8,
V12 etc) and not using the char ones. As a sample
Dear R users:
I would like to assign sequence numbers based on group of value but
cannot find an easy way.
Here is a simple instance:
id = c('a','a','a','b','c','c')
id
[1] a a a b c c
I hope to create a corresponding vector as --
[1] 1 2 3 1 1 2
That is, in group a the
id
[1] a a a b c c
x - split(id, id) # separate by unique values
x - lapply(x, seq) # generate the sequence numbers
x
$a
[1] 1 2 3
$b
[1] 1
$c
[1] 1 2
x - unsplit(x, id) # make back into a vector
x
[1] 1 2 3 1 1 2
On 6/10/06, Tony Chu [EMAIL PROTECTED] wrote:
Dear R users:
I
I heared some project use Perl to analysis log file. And I don't think
it's suit to analysis log file for R.
On 6/11/06, Gabriel Diaz [EMAIL PROTECTED] wrote:
Hello,
Is there any software project that uses R to do log file analisys?
thanks
gabi
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