Response to 1You need the log version e.g. in maximum likelihood, otherwise the
product of the densities and probabilities can become very small.
Ursprüngliche Nachricht Von: r-help-requ...@r-project.org
Datum: 04.08.21 12:01 (GMT+01:00) An: r-help@r-project.org Betreff:
.
Best wishes,
Matthias
PS. Sorry for the HTML email. I’ve given up trying to fix such behavior.
Von: Martin Maechler
Gesendet: Dienstag, 13. Juli 2021 09:09
An: Matthias Gondan
Cc: r-help@r-project.org
Betreff: Re: [R] density with weights missing values
>>>>>
: 12.07.21 18:44 (GMT+01:00) An:
r-help@r-project.org, matthias-gondan , Bert Gunter
Cc: r-help@r-project.org Betreff: Re: [R] density with
weights missing values Sure, you might think that.But most likely the reason
this code has not been corrected is that when you give weights for missing data
?
Ursprüngliche Nachricht Von: Bert Gunter
Datum: 12.07.21 16:25 (GMT+01:00) An: Matthias
Gondan Cc: r-help@r-project.org Betreff: Re: [R]
density with weights missing values The behavior is as documented
AFAICS.na.rmlogical; if TRUE, missing values are removed from x. If FALSE
anymissing values
a.rm=TRUE)
[1] 2
Von: Richard O'Keefe
Gesendet: Montag, 12. Juli 2021 13:18
An: Matthias Gondan
Betreff: Re: [R] density with weights missing values
Does your copy of R say that the weights must add up to 1?
?density doesn't say that in mine. But it does check.
On Mon, 12 Jul 2021 at 22:42,
Dear R users,
This works as expected:
• plot(density(c(1,2, 3, 4, 5, NA), na.rm=TRUE))
This raises an error
• plot(density(c(1,2, 3, 4, 5, NA), na.rm=TRUE, weights=c(1, 1, 1, 1, 1, 1)))
• plot(density(c(1,2, 3, 4, 5, NA), na.rm=TRUE, weights=c(1, 1, 1, 1, 1, NA)))
This seems to work (it
Dear R friends,
I am currently trying to write a piece of C code that uses „embedded R“, and
for specific reasons*, I cannot keep track if R already has been initialized.
So the code snippet looks like this:
LibExtern char *R_TempDir;
if(R_TempDir == NULL)
…throw exception R not
So, I’ll stick with R. Still 25 years or so until retirement, but I’ll survive,
even without crossreferenced default arguments.
Best wishes,
Matthias
Von: S Ellison
Gesendet: Dienstag, 5. September 2017 16:17
An: Matthias Gondan; r-help@r-project.org
Betreff: RE: [R] Strange lazy evaluation of de
mu=0.53, sigma2=4.3^2) # instead of l=u
And maybe also „in-place“ changes of values…
Best regards,
Matthias
Von: William Dunlap
Gesendet: Samstag, 2. September 2017 19:41
An: Rui Barradas
Cc: Matthias Gondan; r-help@r-project.org
Betreff: Re: [R] Strange lazy evaluation of default argume
Dear R developers,
sessionInfo() below
Please have a look at the following two versions of the same function:
1. Intended behavior:
> Su1 = function(u=100, l=u, mu=0.53, sigma2=4.3^2)
+ {
+ print(c(u, l, mu)) # here, l is set to u’s value
+ u = u/sqrt(sigma2)
+ l = l/sqrt(sigma2)
+ mu
I found it:
quantile(ordered(1:10), probs=0.5, type=1)
works, because type=1 seems to round up or down, whatever. The default option
for is 7, which wants to interpolate, and then produces the error.
Two options come to my mind:
- The error message could be improved.
- The default type
Dear R users,
This works:
quantile(1:10, probs=0.5)
This fails (obviously):
quantile(factor(1:10), probs=0.5)
But why do quantiles for ordered factors not work either?
quantile(ordered(1:10), probs=0.5)
Is it because interpolation (see the optional type argument) is not defined? Is
there
The warning
1: In (ind.c == TRUE) (ind.sgn == TRUE) :
longer object length is not a multiple of shorter object length
means that ind.c and ind.sgn have different lengths, for whatever reason.
Although R continues the routine, the warning should, in general, not be
ignored.
Try:
1:3 + 1:2
, Inf)[as a replacement for NULL/
autoselection] and ylim=c(Inf, -Inf)[autoselection, reversed y axis] should be
handled correctly.
I would find such a feature useful. Do you think it would interfere with other
functions?
Thank you for your consideration.
Best wishes,
Matthias Gondan
you might to do something like
library(SuppDists)
t = runif(100, 100, 500) # original RT
t_IG = qinvGauss(ecdf(t)(t)-0.5/length(t), 1, 16)
plot(density(t_IG))
but what is the purpose of it? Usually reaction times are thought to
follow a certain kind of distribution (e.g. an inverse Gaussian
My vote:
1. Symbolic function arguments:
fn = function(a, b)
{
a/b
}
fn(b=10, a=2)
2. Names for elements of a vector and matrices
v = c(a=1, b=2)
v['a'] = v['a'] * 2
same for matrices
3. about 10,000 user-contributed packages on CRAN
4. weird things like
a = numeric(10)
a[1:10] = 1:2
leg.lwd
Best wishes,
Matthias Gondan
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and provide commented, minimal, self-contained
Dear R team, dear Prof. Therneau,
library(survival)
data(colon)
?colon
gives me only a very rudimentary source (only a name). Is there a
possibility to get a reference to the clinical trial these data
are taken from?
Many thanks in advance. With best wishes,
Matthias Gondan
Hi,
Use offset variables if count occurrences of an event and you want to
model the
observation time.
glm(count ~ predictors + offset(log(observation_time)), family=poisson)
If you want to compare durations, look at library(survival), ?coxph
If tnoise_sqrt is the square root of tourist noise,
Hi Ben,
Thanks for clarifying this, I used a misleading word, model the
observation time
sounds as if observation time were the dependent variable - which it is
not, of course,
instead, in the scenario described, the parrot counts are modeled.
Best wishes,
Matthias
Am 30.12.2011 20:50,
Dear R developers,
I want to draw an arrow in a figure with lty=2. The
lty argument also affects the edge of the arrow, which is
unfortunate. Feature or bug?
Is there some way to draw an arrow with intact edge, still
with lty=2?
Example code:
plot(1:10)
arrows(4, 5, 6, 7, lty=2)
Best wishes,
Dear R people,
On my freshly installed R-2.13.1 (winxp), the following code yields
unsatisfactory results (irregular grid lines instead of a smooth plane):
image(matrix(1, nrow=100, ncol=100))
This is working fine,
image(matrix(1, nrow=100, ncol=100), useRaster=TRUE)
but then right-click and
0.8830174
Best wishes,
Matthias Gondan
--
GMX DSL Doppel-Flat ab 19,99 Euro/mtl.! Jetzt mit
gratis Handy-Flat! http://portal.gmx.net/de/go/dsl
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PLEASE do read the posting
On 06/08/10 15:12, Matthias Gondan wrote:
Dear List,
I am aware this is slightly off-topic, but I am sure there are people
who already had the problem and who perhaps solved it.
I am running long-lasting model fits using constrOptim command. At work
there is a linux computer (Quad Core, debian
try this (package Rsolnp)
library(Rsolnp)
g- function(x)
{
return(x[1]^2+x[2]^2)
} # constraint
f- function(x)
{
return(x[1]+x[2])
} # objective function
x0 = c(1, 1)
solnp(x0, fun=f, eqfun=g, eqB=c(1))
Am 10.08.2010 14:59, schrieb Gildas Mazo:
Thanks, but I still cannot get to
try command solnp in package Rsolnp
Am 09.08.2010 18:56, schrieb Dwayne Blind:
Hi !
Why not constrOptim ?
Dwayne
2010/8/9 Gildas Mazogildas.m...@curie.fr
Dear R users,
I'm looking for tools to perform optimization subject to constraints,
both linear and non-linear. I don't mind which
.
Searching around the internet was not very encourageing. Some people
wrote that it is not so simple to have Atlas fully exploit a multicore
computer.
I hope this is not too unspecific.
Best wishes,
Matthias
--
Dr. rer. nat. Matthias Gondan
Institut für Psychologie
Universität Regensburg
D-93050
Brunner et al. available on his website
http://www.ams.med.uni-goettingen.de/de/sof/ld/index.html
But they seem not to be working with current R versions.
Best regards,
Matthias Gondan
--
Sicherer, schneller und einfacher. Die aktuellen Internet-Browser -
jetzt kostenlos herunterladen! http
Dear R developers,
A great R feature is that elements of vectors, lists and dataframes can
have names:
vx = c(a=1, b=2)
lx = list(a=1, b=2)
Accessing element a of vx: vx['a']
Accessing element a of lx: lx[['a']] or lx$a
Might be a matter of taste, but I like the $ very much. Unfortunately,
. Matthias Gondan
Institut für Psychologie
Universität Regensburg
D-93050 Regensburg
Tel. 0941-943-3856
Fax 0941-943-3233
Email: matthias.gon...@psychologie.uni-regensburg.de
http://www.psychologie.uni-r.de/Greenlee/team/gondan/gondan.html
__
R-help@r
Dear R-Users,
Is anyone aware of a significance test which allows
demonstrating that one distribution dominates another?
Let F(t) and G(t) be two distribution functions, the
alternative hypothesis would be something like:
F(t) = G(t), for all t
null hypothesis: F(t) G(t), for some t.
Best
Dear list,
Apparently, there is no function like sscanf in R.
I have a string, Condition: 311, and I would like
to read out the number and store it to a numeric
variable. Is there an easy way to do this?
Best wishes,
Matthias
--
__
Dear list,
I hope the topic is of sufficient interest, because it is not
R-related. I have N=100 yes/no-responses from a psychophysics
paradigm (say Y Yes and 100-Y No-Responses). I want to see
whether these yes-no-responses are in line with a model
predicting a certain amount p of
Dear list,
I think there is a small bug in the constrOptim documentation (R-2.7.0):
## from optim
fr - function(x) { ## Rosenbrock Banana function
x1 - x[1]
x2 - x[2]
100 * (x2 - x1 * x1)^2 + (1 - x1)^2
}
grr - function(x) { ## Gradient of 'fr'
x1 - x[1]
x2 - x[2]
Hi Geoff,
I think the answer to such a problem (overall survival vs. disease free
survival) depends on the regulatory
environment, for example, in a phase III clinical trial, OS would be
used, whereas in an equivalence study,
DFS would be used.
Best,
Matthias
Geoff Russell schrieb:
Dear
Hi Eleni, hi list,
here is small sample program, the library is survival, it is included
in the standard R distribution.
data(colon)
s = survfit(Surv(time, status) ~ rx, data=colon)
plot(s)
plot(s, col=1:3)
By the way: Does anyone know a neat way to indicate the number of
patients under
Dear list,
Is anyone aware of a library for sample size calculation in R, similar
to NQuery? I have to give a course in this area, and I would like to
enable the students playing around with this.
Best wishes,
Matthias
__
R-help@r-project.org mailing
Hi Eleni,
The problem of this approach is easily explained: Under the Null
hypothesis, the P values
of a significance test are random variables, uniformly distributed in
the interval [0, 1]. It
is easily seen that the lowest of these P values is not any 'better'
than the highest of the
P
.
On Feb 13, 2008 4:52 AM, Matthias Gondan [EMAIL PROTECTED] wrote:
Dear list,
Is anyone aware of a library for sample size calculation in R, similar
to NQuery? I have to give a course in this area, and I would like to
enable the students playing around with this.
Best wishes
(little correction below)
Dear list,
This is off-topic, but perhaps there is an expert out there who can help
me in
a bootstrapping test.
I have two samples A, B from, say, a normal distribution. A third sample R
is the vector of pairwise minima of the same random variables:
A =
Dear list,
This is off-topic, but perhaps there is an expert out there who can help
me in
a bootstrapping test.
I have two samples A, B from, say, a normal distribution. A third sample R
is the vector of pairwise minima of the same random variables:
A = rnorm(100)
B = rnorm(100)
A2 =
Hi Diana,
Look at Edgar Brunner's Homepage
http://www.ams.med.uni-goettingen.de/en/sta/e.brunner.html
and here:
http://www.ams.med.uni-goettingen.de/en/sof/index.html
Unfortunately, the R script for a 2x2 design with two groups and two
timepoints (f1.ld.f1.r) seems to be broken. Uncommenting
Dear List,
I have tried a stratified Cox Regression, it is working fine, except for
the Anova-Tests:
Here the commands (should work out of the box):
library(survival)
d = colon[colon$etype==2, ]
m = coxph(Surv(time, status) ~ strata(sex) + rx, data=d)
summary(m)
# Printout ok
anova(m,
Dear R users,
I noticed a problem in the anova command when applied on
a single coxph object if there are missing observations in
the data:
This example code was run on R-2.6.1:
library(survival)
data(colon)
colondeath = colon[colon$etype==2, ]
m = coxph(Surv(time, status) ~ rx + sex +
lines. A bug in R? (Windows binary, 2.6.0)
Best wishes,
Matthias Gondan
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