Hi,
I am wondering whether there is a function that could plot
a dot diagram like the output of following code.
Thanks in advance!
Best wishes!
Jinsong
-my dirty code here-
mydata - c(26,26,27,27,27,27,28,28,28,28,28,28,28,28,28,
Louis,
OK, I don't use any GUI, just the command line. Everything works fine on the
command line.
I had the same problem with downloaded Suse 10. It doesn't contain all the
same packages that the purchased version does. You have to do Yast /
Installation Source and add installation sources.
Thanks for the brilliant solution.
***AGAIN***
Now - just to go deeper into the **same subject** on which I'm really supposed
to work very soon - if I want to aggregate by date only data, say, before
noon (12.00.00) what should I do?
Ciao
Vittorio
Alle 16:13, venerdì 07 aprile 2006, Whit
Any one can explain why this happens or any work arounds?
setClass('foo')
[1] foo
setAs('foo', 'character', function(from) from)
showMethods('coerce')
Function coerce:
from = ANY, to = array
from = ANY, to = call
from = ANY, to = character
from = ANY, to = complex
from = ANY, to = environment
Matt Goff goff at nawwal.org writes:
The problem is that boxplot is displaying groups that are empty in the
plot.
Call factor() again on the groups, which will drop levels. You can do that in an
extra line, or on-the-fly:
data-data.frame(values=c(1:25), groups=rep(c(A,B,C,D,E),
Andreas Svensson andreas.svensson at bio.ntnu.no writes:
I had a suspicion that you can't have the lme4 package loaded when using
lme (from the nlme package), and lo! I get the full summary of lme only
if lme4 is NOT loaded.
Yes, currently the two don't coexist well, so better make sure
G. Alex Janevski galexski at umich.edu writes:
points(y~x, pch=*, col=black)
lm(y~x)
fm=lm(y~x)
abline(fm, col=red)
This works. The problem arises in that I would like to run my simulation
multiple times, to plot the data points together on the same plot, and
more importantly the
It is recommended that you use a package for this sort of thing.
When a package is loaded, the S4 methods it contains are merged into the
metadata. When the global environment is loaded, they are not. Call
'cacheMetaData(1)' to do so.
[This looks like a bug: cacheMetaData is called on
Matt Goff wrote:
I am trying to use the formula interface for the boxplot.
Currently running R 2.2.1 on Windows XP.
The problem is that boxplot is displaying groups that are empty in the
plot.
The following example demonstrates what it is happening (though my actual
situation is a
How one can make a list of all functions in R's base
package which are given as Primitives like abs, sqrt
cumsum (but not log) ?
Thanks a lot
Diethelm Wuertz
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New e-mail address: [EMAIL PROTECTED]
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On 4/9/2006 5:46 AM, Diethelm Wuertz wrote:
How one can make a list of all functions in R's base
package which are given as Primitives like abs, sqrt
cumsum (but not log) ?
There's an is.primitive() test function; you just need to get all
objects, and test them one by one.
Duncan Murdoch
2006/4/8, He, Yulei [EMAIL PROTECTED]:
Hi, there.
How do I calculate the cross-product in the form of
\sum_{i=1}^{n}X_{i}^{t} \Sigma X_{i} using R code without using do loop?
X_{i} is the covariate matrix for subject I, \Sigma is the covariance
matrix.
If I don't miss something in the
Dear Bill,
You might check Faraway's 'Extending the Linear Model with R:
Generalized Linear, Mixed Effects and Nonparametric Regression Models'
(2006). Without having read the book properly, at least I noticed that
package lme4 and the function lmer is used in the examples.
Best regards,
R^2 for a model is usually defined as 1-RSS/TSS where TSS is the SS
about the mean and RSS is the residual SS from the model.
Consider the model in R
z - runif(20)
y - z+rnorm(20)
my.model - lm(y~offset(z))
summary(my.model)$r.squared
Here the RSS is equivalent to the TSS and
gives 0 when it
Don't know about a function but it can be done in one plot statement
like this:
plot(seq(x) - match(x, x) ~ x, list(x = sort(mydata)),
xlim=c(25,45), ylab =, yaxt=n, pch=19, frame.plot=FALSE)
On 4/9/06, Jinsong Zhao [EMAIL PROTECTED] wrote:
Hi,
I am wondering whether there is a
Hi All,
This is probably a very simple question. I was trying to add a row to the
rows in a matrix. For example:
a - matrix(1:6,2,3)
b - a[1,]
print(a)
[,1] [,2] [,3]
[1,]135
[2,]246
print(b)
[1] 1 3 5
I now want to add 'b' to every row of 'a',
I haven't heard any more comments on this, and R 2.3.0 is almost here,
so I'll bring this thread to a close. I have changed the default theme
to the old PDF default for all devices (except postscript, which still
defaults to color=FALSE) in the latest lattice (part of R-alpha now).
It's easy
You can try sweep:
sweep(a,2,b,+)
-Christos
-Original Message-
From: [EMAIL PROTECTED]
[mailto:[EMAIL PROTECTED] On Behalf Of Tim Smith
Sent: Sunday, April 09, 2006 11:28 AM
To: r-help@stat.math.ethz.ch
Subject: [R] adding a row to a matrix
Hi All,
This is probably a very simple
*I've been trying for several weeks to install R-2.2.1 on a PC with
an AMD Athlon 64 2800*+* processor running Mandriva 2006_64. After
unpacking R-2.2.1.tar.gz I ran ./configure. However, configure stopped
prematurely with the message *configure:27295: WARNING: gfortran and
gcc disagree on
Hi ..
lm() returns an effects component in its output. I read the explanation in
R but was not quite clear.
say my response is Y
and design matrix is X
say X has QR decomposition X=QR
is effects = Q (Q'Q)^-1 Q' Y ???
i am sure this is wrong as it did not match the
On Sunday 09 April 2006 11:41, R. A. L. Carter wrote:
prematurely with the message *configure:27295: WARNING: gfortran and
gcc disagree on int and double configure:27297: error: Maybe change
CFLAGS or FFLAGS?* Altough I've looked in both the R_Help archive and
This is primarily a guess, but
When fitting a logistic regression model using weights I get the
following warning
data.model.w - glm(ABN ~ TR, family=binomial(logit), weights=WEIGHT)
Warning message:
non-integer #successes in a binomial glm! in: eval(expr, envir, enclos)
Details follow
***
I have a binary dependent
Try this:
t(t(a)+b)
On 4/9/06, Tim Smith [EMAIL PROTECTED] wrote:
Hi All,
This is probably a very simple question. I was trying to add a row to the
rows in a matrix. For example:
a - matrix(1:6,2,3)
b - a[1,]
print(a)
[,1] [,2] [,3]
[1,]135
[2,]246
I am having some problems using the latex() function in the Hmisc
package. When I turned on the ctable option in latex(), the LaTeX
code produced by latex()somehow conflicts with the style back my
unversity uses for theses. Has anyone on the list had a similar
conflict and been able to fix it.
Just strip off the hours component of the dates, then take a subset of the data
where the hour is = 12.
I did not execute this, so you might need to change it a bit:
hours - as.integer(format(dates(base),%H))
new.data - base[hours = 12,]
Thanks Christosworked a treat!
Christos Hatzis [EMAIL PROTECTED] wrote: You can try sweep:
sweep(a,2,b,+)
-Christos
-Original Message-
From: [EMAIL PROTECTED]
[mailto:[EMAIL PROTECTED] On Behalf Of Tim Smith
Sent: Sunday, April 09, 2006 11:28 AM
To: r-help@stat.math.ethz.ch
Hi, I am writing a function that includes 'sum' function
such as:
f-function(x){
c-c(-1,0,1)
f-sum(c+x)
}
expecting f to be -1+x+0+x+1+x=3x. But I found out that f is
sum(x). So, f is always a scalar, which means that f(c(0,1))
is not a vector as c(0,3), but 3(0+1)=3. I would like to ask
you
If c is c(c1, c2, c3) and x is c(x1, x2, x3) then
c+x is (c1+x1, c2+x2, c3+x3)
so sum(c+x) is c1+x1+c2+x2+c3+x3 = sum(c) + sum(x)
What you were expecting is given by:
rowSums(outer(1:4, c(-1,0,1), +)) # gives c(3, 6, 9, 12)
Review the Introduction to R manual and also look at ?outer and
Or, of course, if you are willing to reduce it then its just
sum(c) + length(c) * x
On 4/9/06, Gabor Grothendieck [EMAIL PROTECTED] wrote:
If c is c(c1, c2, c3) and x is c(x1, x2, x3) then
c+x is (c1+x1, c2+x2, c3+x3)
so sum(c+x) is c1+x1+c2+x2+c3+x3 = sum(c) + sum(x)
What you were
Duncan Murdoch wrote:
On 4/9/2006 5:46 AM, Diethelm Wuertz wrote:
How one can make a list of all functions in R's base
package which are given as Primitives like abs, sqrt
cumsum (but not log) ?
There's an is.primitive() test function; you just need to
Sorry when I ask again, how to
Dear R users
This is a stats question rather than R question. For continuous predictors, we
get estimates of slopes and their se and t values (slope/se) in R ouptput. If
we have a model with more than one continuous variable (i.e., multiple
regression), we get slope, se and t value for each
On 4/9/2006 5:57 PM, Diethelm Wuertz wrote:
Duncan Murdoch wrote:
On 4/9/2006 5:46 AM, Diethelm Wuertz wrote:
How one can make a list of all functions in R's base
package which are given as Primitives like abs, sqrt
cumsum (but not log) ?
There's an is.primitive() test function; you just
Dear R list,
I have fitted cubic regression spline with fixed degree of freedom to a
set of data using package mgcv. Now I want to calculate the area under the
spline curve. Someone has suggested me to use trapezoidal rule. Do you know
if someone has written a package that will carry out that
I am wondering how to obtain SE estimates for fixed effects from a nonlinear
mixed effects model?
I have fixed effects corresponding to three factors A, B and C with 2, 3 and 3
levels respectively. I have fit a model of the following general form:
nlme1-nlme(y~ SasympOrig(x, Asym, lrc),
Hi, thanks for your reply.
Here I would like to ask you again more directly.
The following is what I had for now.
The function to begin with is
dnorm(theta+2*pi*j,0,1)*(pnorm(((2*pi*(k+1)-rho*
(theta+2*pi*j)).
Now, I wanted to sum it over k from -1 to 1. So, I
wrote the following.
Weighted spatial kernel density estimation is available in
the function 'density.ppp' in the package 'spatstat'.
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PLEASE do read the posting guide!
Greetings,
I have had good success using the clara() function to perform a simple cluster
analysis on a large dataset (1 million+ records with 9 variables).
Since the clara function is a wrapper to pam(), which will accept known medoid
data - I am wondering if this too is possible with
I encounter a statistic problem about correlation.
I use R to test wether two variables are correlated or not.
(pearson correlation)
cor.test(x,y) give a p=5.87
Because the x, y is not normal distributed (qqplot indicate that) I
also perform
(spearman
Try this where g is f summed over j and k for given scalars
theta and rho and gv is g vectorized over theta. I have not
checked this carefully so be sure you do:
f - function(theta = 0, rho = 0, j = 0, k = 0)
dnorm(theta+2*pi*j,0,1)*pnorm(2*pi*(k+1)-rho*(theta+2*pi*j))
g - function(theta
Sorry, I replied to the wrong email. Here it is again:
Try this where g is f summed over j and k for given scalars
theta and rho and gv is g vectorized over theta. I have not
checked this carefully so be sure you do:
f - function(theta = 0, rho = 0, j = 0, k = 0)
Hello all,
I have the code below to simulate samples of certain size from a
particular distribution (here,beta distribution) and compute some
statistics for the samples.
betasim2-function(nsim,n,alpha,beta)
{
sim-matrix(rbeta(nsim*n,alpha,beta),ncol=n)
xmean-apply(sim,1,mean)
hello
I wonder if anyone can tell me the logic of using of interactive
parameters in
logistic regression ? (or direct me any link containing explaining it)
kind regards
Ahmet Temiz
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