well, for a simple stripchart (i.e., default method) you can use
something like the following:
x <- rnorm(9)
cl <- c(1,1,1,2,2,2,3,3,3)
plot(range(x), c(0, 1), type = "n", yaxt = "n", ann = FALSE)
points(x, rep(0.5, length(x)), pch = cl)
I hope it helps.
Best,
Dimitris
Sam Player wrote:
If
If I have a dataset grouped into 3 classes, how can I construct a
stripchart where the markers are different for each class, e.g. a cross
for 1, square for 2 and circle for 3. In the example below I try to
define the marker type by the class but this only changes all the
markers from the defaul
A fine answer, and indeed I am aware of the option to leave the model empty.
I like the option of consistently not being protected from myself.
That said, some other R functions (predict comes to mind) use $model if it
exists (which it usually does, though needn't) but allow new (or "other")
data
Try:
mydata[substr(rownames(mydata),1,1)!="U",]
where mydata is a matrix or data.frame.
Daniel Moreira, MD
"Sally"
Sent by: r-help-boun...@r-project.org
02/14/2009 11:48 PM
Please respond to
Sally
To
cc
Sally
Subject
[R] Delete row if first let
Hello!
I am still a beginner. Can you tell me how to delete a row (from a matrix or
data.frame) if the row name starts with U? See example below:
U179971039 0.0586630.087575
empty1 -0.1296 -0.09105
empty2 0.136259 0.398073
empty3 0.446041 -0.33997
Sally
I have been trying to write a new class that reimplements the vector
class. As a test of my overloading I decided to try and and call
t.test on two vectors which were objects of my class rather than the
default class.
The overloaded length I wrote seems to work correctly. I used
setMethod("length
It's pretty simple. In R, objects are stored im memory. If the objects are
big, they take up a lot of memory. If your data frame is big, the objects are
big too.
The problem really only arises commonly if you are fitting many models
simultaneously and holding them all in memory at once, but
Could you explain how memory problems may arise? I understand that by
using model=FALSE, we can reduce the memory required. But if we did
not, what kinds of problems may arise. I have run into a possible
memory leak that I have not been able to work around (using yags, not
lm). I am trying to gain
Without arguing you case I would point out that the data need not be there in
l$model:
> l <- lm(y ~ x, data=ex, model = FALSE)
> l
Call:
lm(formula = y ~ x, data = ex, model = FALSE)
Coefficients:
(Intercept)x
0.1310 -0.1736
> l$model
NULL
Model objects are often hu
Hi,
I'm playing around with stepwise regression, using the step
function, and believe I have found a bug (or at least, a strong case for
improvement):
ex <- data.frame(y=rnorm(100),x=rnorm(100))
l <- lm(y ~ x, data=ex)
step(l)
[output is correct]
rm(ex)
step(l)
Start: AIC=11.79
y ~
The regression book by John Fox:
http://socserv.mcmaster.ca/jfox/Books/Companion/index.html
has a section on regression diagnostics and everything is done
in R which might make it particularly suitable.
On Sat, Feb 14, 2009 at 6:48 PM, Jason Rupert wrote:
> Many thanks to Greg L. Snow and David W
John Malone wrote:
Hi!
I'm trying to implement an outlier test once/row in a large dataframe.
Ideally, I'd do this then add the Pvalue results and the number flagged as
an outlier as two new separate columns to the dataframe. Grubbs outlier
test requires a vector and I'm confused how to make ea
Many thanks to Greg L. Snow and David Winsemius for their responses.
First off I can safely say I don't know enough statistics to be dangerous, but
hopefully I will get to that point:)
Regarding the goal - ultimately I would like to use linear regression
(constrained for using linear regress
Sending each row of a datatframe, dfm, as a vector to a function,
fcn, is as simple as;
apply(dfm, 1, fcn)
e.g.:
> dfm <- data.frame(x=rnorm(10), y=rnorm(10), z=rnorm(10))
>
> apply(dfm, 1, sum)
[1] 0.7385838 -3.1819193 0.3415670 -0.6552601 -1.3470174
-0.6446259 -0.6544967
[8] 0.1778
Hi!
I'm trying to implement an outlier test once/row in a large dataframe.
Ideally, I'd do this then add the Pvalue results and the number flagged as
an outlier as two new separate columns to the dataframe. Grubbs outlier
test requires a vector and I'm confused how to make each row of my datafram
Hi Hans - I tried your suggestion and it worked out well... Many thanks!!
Also, thank to everyone else for their suggestions.
Hans W. Borchers-4 wrote:
>
> Pele yahoo.com> writes:
>
>>
>>
>> Hello R users,
>>
>> Can someone tell if there is a package in R that can do outlier detection
>>
The help file for grid.line.to says that Grid has the notion of a current
location. Is there a way to get that current location? I looked for a function
that returns this but I didn't find anything.
Basically, I'm looking to do something like turtle graphics and I need to write
a function like g
knussear wrote:
>
> Yes, fair enough. I wasn't sure it was fitting the mode at all, but here
> is an example of what I see
>
>> model <- betareg(ACT ~ ST+DOY, data = actDL_F)
> Warning messages:
> 1: In sqrt(diag(fisherinv)) : NaNs produced
> 2: In sqrt(diag(fisherinv)) : NaNs produced
> 3: In
Yes, fair enough. I wasn't sure it was fitting the mode at all, but here is
an example of what I see
> model <- betareg(ACT ~ ST+DOY, data = actDL_F)
Warning messages:
1: In sqrt(diag(fisherinv)) : NaNs produced
2: In sqrt(diag(fisherinv)) : NaNs produced
3: In sqrt(W) : NaNs produced
4: In sqrt(
knussear mac.com> writes:
>
>
> Hi
>
> I'm trying to fit a model in betareg and I'm getting errors, but have no
> idea what they mean or how to solve them. Does anyone have experience with
> this?
>
> > model <- betareg(ACT ~ ST*SoilT, data = actDL_F)
> Warning messages:
> 1: In sqrt(W) : NaN
Hi all,
Could you please email me off-list if you'd be interested (and able)
in attending a regular R meetup in Houston. Very tentatively it would
be held the last Monday or Wednesday of the month, 5-6:30pm at Rice
University. It could be as formal as informal as you like, but I'm
imagining a so
On Feb 14, 2009, at 3:23 AM, Thomas Lumley wrote:
On Fri, 13 Feb 2009, David Winsemius wrote:
I must disagree with both this general characterization of the
Wilcoxon test and with the specific example offered. First, we
ought to spell the author's correctly and then clarify that it is
th
All Bay Area useR's,
Quick reminder that our use R! Group 2009 kick off meeting is next
Wednesday evening: http://www.meetup.com/R-Users/calendar/9573566/ at
Predictive Analytics World.
Panel Discussion - The R and Science of Predictive Analytics: Four
Case Studies in R
* Bo Cowgill, Google
Dear Tal,
> -Original Message-
> From: Tal Galili [mailto:tal.gal...@gmail.com]
> Sent: February-14-09 10:23 AM
> To: John Fox
> Cc: Peter Dalgaard; Nils Skotara; r-help@r-project.org; Michael Friendly
> Subject: Re: [R] Anova and unbalanced designs
>
> Hello John and other R mailing list
Doug Martin et al ( he may not be the first author ) has a book called
Robust Regression
and I vaguely recall seeing a chapter in there related to outlier
detection. in time series.
Given that there's an S+ package associated with the book, maybe that
package has been or can be translated to
Check out the Tramo Seats and Gretl packages. These are not
R packages but are free. The first one has outlier detection
and the second has interfaces to both Tramo Seats and R which may
or may not allow you to access Tramo Seats indirectly from R.
On Sat, Feb 14, 2009 at 8:15 AM, Pele wrote:
>
Hello John and other R mailing list members.
I've been following your discussions regarding the Anova command for the SS
type 2/3 repeated measures Anova, and I have a question:
I found that when I go from using type II to using type III, the summary
model is suddenly added with an "intercept" te
Daniel Moreira wrote:
Rodrigo,
Wilcoxon?Mann?Whitney allows arbitrary sample sizes. It is an extension of
the original Wilcoxon test which only handles equal sample sizes.
Daniel Moreira, MD
I believe you'll find that the Wilcoxon 2-sample test alway
Rodrigo,
Wilcoxon?Mann?Whitney allows arbitrary sample sizes. It is an extension of
the original Wilcoxon test which only handles equal sample sizes.
Daniel Moreira, MD
Research Associate
Duke University Medical Center
DUMC 2626, MSRB-I Room 455
571 Rese
Hi,
I have a statistical question.
To apply the Mann Whitney test to compare a pair of vectors, they must to
have the same length ?
Thanks,
Rodrigo
[[alternative HTML version deleted]]
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R-help@r-project.org mailing list
https://stat.ethz.c
Pele yahoo.com> writes:
>
>
> Hello R users,
>
> Can someone tell if there is a package in R that can do outlier detection
> that give outputs simiilar to what I got from SAS below.
>
> Many thanks in advance for any help!
I guess you are talking about the OUTLIER procedure in SAS that att
Hi Stephen,
I am doing cross correlation analysis and I am trying to find a outlier
detection function in R that can detect changes in the level of the response
series that are not accounted for by the estimated model. Something that
tells whether the changes are considered Additive Outliers, Lev
On 13/02/2009 11:59 PM, Roger wrote:
Hello,
I have a weird problem here. What I want to do is that I need to draw 1000
samples from a matrix, and use glm on them.
when I used this command, it runs without the problem
qdata.glm = glm(X258 ~ ., family = binomial, data =
q2data[sample(dim(q2dat
Hello,
I have a weird problem here. What I want to do is that I need to draw 1000
samples from a matrix, and use glm on them.
when I used this command, it runs without the problem
> qdata.glm = glm(X258 ~ ., family = binomial, data =
q2data[sample(dim(q2data)[1], 1000), ])
but if I drew the sa
Hi Tanveer,
the PLM package includes the possibility to estimate instrumental variable
models. It also includes a function PGMM to estimate GMM models. Try
?pgmm... By the way, if you manage to make this function work, I'd be glad
for a quick note. I've been ecountering massive problems with this
Hi!
I am quite a new user of R. I wanted to ask if there was some package
for dynamic panel analysis (with Arneallo-Bond Method) like stata. PLM
is for panel analysis but not for dynamic.
Best regards,
Tanveer
__
R-help@r-project.org mailing list
Hi Everybody,
If I build a latent class model using lca or flexmix, how can I use the result
to score another set of data and get predictions for class membership for that
other set of data? I don't see a predict. function for lca or flexmix.
Help would be much appreciated.
--John Sparks
On Fri, 13 Feb 2009, David Winsemius wrote:
I must disagree with both this general characterization of the Wilcoxon test
and with the specific example offered. First, we ought to spell the author's
correctly and then clarify that it is the Wilcoxon rank-sum test that is being
considered. Next,
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