Displaying 20 results from an estimated 8000 matches similar to: "Suggestion to extend aggregate() to return multiple and/or named values"
2007 Sep 27
3
Aggregate factor names
Hi all,
A suggestion derived from discussions amongst a number of R users in
my research group: set the default column names produced by aggregate
() equal to the names of the objects in the list passed to the 'by'
object.
ex. it is annoying to type
with(
my.data
,aggregate(
my.dv
,list(
one.iv = one.iv
,another.iv = another.iv
,yet.another.iv = yet.another.iv
)
2007 Jun 26
2
Power calculation with measurement error
Hi all,
Hopefully this will be quick, I'm looking for pointers to packages/
functions that would allow me to calculate the power of a t.test when
the DV has measurement error. That is, I understand that, ceteris
paribus, experiments using measure with more error (lower
reliability) will have lower power.
Mike
--
Mike Lawrence
Graduate Student, Department of Psychology, Dalhousie
2007 Oct 01
3
optimize() stuck in local plateau ?
Hi all,
Consider the following function:
####
my.func = function(x){
y=ifelse(x>-.5,0,ifelse(x< -.8,abs(x)/2,abs(x)))
print(c(x,y)) #print what was tested and what the result is
return(y)
}
curve(my.func,from=-1,1)
####
When I attempt to find the maximum of this function, which should be
-.8, I find that optimize gets stuck in the plateau area and doesn't
bother testing the
2007 Aug 08
3
SWF animation method
Hi all,
Just thought I'd share something I discovered last night. I was
interested in creating animations consisting of a series of plots and
after finding very little in the usual sources regarding animation in
R directly, and disliking the imagemagick method described here
(http://tolstoy.newcastle.edu.au/R/help/05/10/13297.html), I
discovered that if one exports the plots to a
2007 Sep 17
1
Create correlated data with skew
Hi all,
I understand that it is simple to create data with a specific
correlation (say, .5) using mvrnorm from the MASS library:
> library(MASS)
> set.seed(1)
>
> a=mvrnorm(
+ n=10
+ ,mu=rep(0,2)
+ ,Sigma=matrix(c(1,.5,.5,1),2,2)
+ ,empirical=T
+ )
> a
[,1] [,2]
[1,] -1.0008380 -1.233467875
[2,] -0.1588633 -0.003410001
[3,] 1.2054727 -0.620558768
2008 May 09
1
lme() with two random effects
Hi all,
I have collected response time data from 178 participants ('sub') for
each combination of 4 within-Ss factors ('con','int','tone','cue').
Additionally, I have recorded the gender of each participant, so this
forms a between-Ss factor ('gender'). Normally this would be analyzed
using aov:
2007 May 24
2
Calculation of ratio distribution properties
Hi all,
Looking to calculate the expected mean and variance of a ratio
distribution where the source distributions are gaussian with known
parameters and sample values are correlated. I see (from wikipedia:
http://en.wikipedia.org/wiki/
Ratio_distribution#Gaussian_ratio_distribution) that this calculation
is quite involved, so I'm hoping that someone has already coded a
function to
2007 Jun 20
2
how to create cumulative histogram from two independent variables?
Hi all,
I am extremely newbie to R. Can anybody jump-start me with any clues as to
how do I get a cumulative histogram from two independent variables,
cumhist(X,Y) ?
-jose
[[alternative HTML version deleted]]
2007 Jun 22
1
connecting to running process possible?
Hello,
i'm trying to find a more modern system to reproduce the functionality that
was available through the Histoscope program (from Fermilab). Namely, the
capability of connecting to a running process and having plots update in
realtime in response to new data. Is this possible with R? Thank you,
Charles Cosse
[[alternative HTML version deleted]]
2007 Jun 26
3
surprising difference in log()
Hello everybody
My collegue and I noticed a strange behaviour of R on different
platforms. It's a simple computation, but results are rather different.
On Windows XP:
> floor(log(8,2))
[1] 3
which is what one should expect.
Here's instead the result with Mac OS X (same version, 2.5.0
(2007-04-23))
> floor(log(8,2))
[1] 2
Is it a "bug" in R or in the operating
2008 Dec 07
5
How to force aggregate to exclude NA ?
The aggregate function does "almost" all that I need to summarize a datasets, except that I can't specify exclusion of NAs without a little bit of hassle.
> set.seed(143)
> m <- data.frame(A=sample(LETTERS[1:5], 20, T), B=sample(LETTERS[1:10], 20, T), C=sample(c(NA, 1:4), 20, T), D=sample(c(NA,1:4), 20, T))
> m
A B C D
1 E I 1 NA
2 A C NA NA
3 D I NA 3
4 C I
2008 Jul 10
2
Lattice: merged strips?
Hi all,
By default a call to xyplot from the Lattice package when using 2
factors [eg xyplot( dv~iv | XY * AB ) ] yields the following shingle
structure:
|_A_|_A_|_B_|_B_|
|_X_|_Y_|_X_|_Y_|
However, I'm wondering if it is possible to merge the upper shingle
within levels of that factor, as in:
|___A___|___B___|
|_X_|_Y_|_X_|_Y_|
Mike
--
Mike Lawrence
Graduate Student, Department of
2007 Jul 26
2
logistic regression
Greetings,
I am working on a logistic regression model in R and I am struggling with the code, as it is a relatively new program for me. In searching Google for 'logistic regression diagnostics' I came Elizabeth Brown's Lecture 14 from her Winter 2004 Biostatistics 515 course (http://courses.washington.edu/b515/l14.pdf) . I found most of the code to be very helpful, but I am
2007 Jul 22
4
using R for a reaction-time experiment
I want to use R to run a reaction-time experiment: Something appears on the
screen, I respond by typing something (one keystroke), the system measures
the speed of my response. R would be great for this if only I didn't have to
hit Enter to enter that keystroke. I am doing such experiments now but they
require two actions per trial: hit keystroke, hit Enter.
Is there some way that R can be
2007 May 30
1
test to compare significant correlation increase
Hi!
I am calculating correlation between two variables:
1. X versus Y
2. X versus Y(with a 3 steps lag)
I would like to test if the correlation
increase/decrease from 1 to 2 is significant or not.
Is there any function in R to do this? any hints?
Thanks for help :)
David Ria?o
Center for Spatial Technologies and Remote Sensing (CSTARS)
University of California
250-N, The Barn
One Shields
2007 May 26
2
polygon error?
Hi.. I'm not sure why polygon returns an area above the standard normal curve.
z <- pretty(c(-3,3), 100)
ht <- dnorm(z)
data <- data.frame(z=z, ht=ht)
zc <- 1.645
plot(data, type="l")
lines(data)
t <- subset(data, z>zc)
polygon(t, col="red")
Thanks,
Lance
[[alternative HTML version deleted]]
2008 Jul 15
1
aov error with large data set
I'm looking to analyze a large data set: a within-Ss 2*2*1500 design
with 20 Ss. However, aov() gives me an error, reproducible as follows:
id = factor(1:20)
a = factor(1:2)
b = factor(1:2)
d = factor(1:1500)
temp = expand.grid(id=id, a=a, b=b, d=d)
temp$y = rnorm(length(temp[, 1])) #generate some random DV data
this_aov = aov(
y~a*b*d+Error(id/(a*b*d))
, data=temp
)
While yields the
2007 Jun 11
3
simultaneous computing
Hello,
which possibilities are available in R for simultaneous or parallel
computing?
I only could find biopara
(http://cran.r-project.org/src/contrib/Descriptions/biopara.html)
Are there other possibilities?
Are there special groups working on simultaneous computing with R?
Thanks
Markus
--
Dipl.-Tech. Math. Markus Schmidberger
Ludwig-Maximilians-Universit?t M?nchen
IBE - Institut f?r
2009 Mar 30
3
Calculating First Occurance by a factor
I'm having difficulty finding a solution to my problem that without using a
for loop. For the amount of data I (will) have, the for loop will probably
be too slow. I tried searching around before posting and couldn't find
anything, hopefully it's not embarrassingly easy.
Consider the data.frame, Data, below
Data
Sub Tr IA FixInx FixTime
p1 t1 1 1 200
p1 t1 2
2008 Jul 17
2
Sampling distribution (PDF & CDF) of correlation
Hi all,
I'm looking for an analytic method to obtain the PDF & CDF of the
sampling distribution of a given correlation (rho) at a given sample
size (N).
I've attached code describing a monte carlo method of achieving this,
and while it is relatively fast, an analytic solution would obviously
be optimal.
get.cors <- function(i, x, y, N){
end=i*N