Displaying 20 results from an estimated 2000 matches similar to: "Top N correlations from 'cor' for very large datasets being run many times"
2010 Mar 05
1
Error in inherits(x, "data.frame") : subscript out of bounds
Hi,
I have a list p with different size dataframes and length of over
8000. I'm trying to
calculate correlations between the rows of dataframes of this list and
columns of another
dataset (type data.frame also) so that first column is correlated with
all the rows in
the list dataframe. Some information from another dataset is also
included to the final
output (all.corrs). This worked a
2007 Jul 20
1
how to determine/assign a numeric vector to "Y" in the cor.test function for spearman's correlations?
Hello to all of you, R-expeRts!
I am trying to compute the cor.test for a matrix that i labelled mydata
according to mydata=read.csv...
then I converted my csv file into a matrix with the
mydata=as.matrix(mydata)
NOW, I need to get the p-values from the correlations...
I can successfully get the spearman's correlation matrix with:
cor(mydata, method="s",
2005 Dec 03
1
Correlation matrix from a vector of pairwise correlations
I've a vector of pairwise correlations in the order low-index element
precedes the high-index element, say:
corr(1,2)=0.1, corr(1,3)=0.2, corr(2,3)=0.3, corr(3,4)=0.4
How can I construct the corresponding correlation matrix?
I tried using the "combn"-function in "combinat" package:
library(combinat)
combn(c(0.1,0.2,0.3,0.4),2)
, but to no avail...
Thank you for your
2006 Feb 01
1
cor/group by???
Can someone help me calculate correlations for grouped values?
Heres what my first few line of data look like:
> head(cmexpr)
LLID GMID CEXPR MEXPR
1 1005 10831 2.057462 -0.08486
2 1005 10831 2.057515 -0.08486
3 1005 10831 2.057462 0.01209
4 1005 10831 2.057515 0.01209
5 1005 10836 2.050980 0.17237
6 1005 10836 2.018576 0.17237
LLID is gene id, GMID is cell line id, the EXPR
2010 May 28
0
Problems executing cor(dataset) function in R 2.11.0 for OSX ( It works fine in R 2.10.1)
Hi all,
I was experiencing a similar problem with some code which uses the package
maCorrPlot (BioConductor)
http://www.bioconductor.org/packages/2.6/bioc/html/maCorrPlot.html
to compute the correlation between different variables. This code was
working
apparently fine under R 2.9 (but it was raising warning messages!) and the
same was not working under R 2.11.
A simple example was:
1.>
2010 Jan 30
2
convert data frame of values into correlation matrix
Hi Group,
Consider a data frame like this:
mylabel1 <- rep(c("A","B","C"),each=3)
mylabel2 <- rep(c("A","B","C"),3)
corrs <- c(1,.8,.7,.8,1,.7,.7,.7,1)
myData <- data.frame(mylabel1,mylabel2,corrs)
myData
mylabel1 mylabel2 corrs
1 A A 1.0
2 A B 0.8
3 A C 0.7
4 B
2004 Aug 06
0
I am away from this office from 24 December 2002, returning 6 January 2003
I will be out of the office starting 24/12/2002 and will not return until
06/01/2003.
You can contact me on 0407 756 568.
<p><p><p><p>------------------------------------------------------------------------------------------------------------------
This e-mail and any attachments may be confidential. You must not disclose or use the information contained in this e-mail
2011 Jun 02
0
allowing individual level correlations to differ by cluster in lme in R
Dear R-listers,
I am fitting bivariate mixed models for cost-effectiveness data of cluster randomized trials using lme in R. So I have individuals nested within clusters. My response variable is a vector with bivariate response (individual level costs and effects) stacked into a single column. The covariates in my models are a constant and a treatment term. They are response-specific, e.g. a
2004 May 25
1
cor and missing values. Bug?
There seems to be an issue in computing rank correlations with missing
values present. I think this comes from the way rank() function works but
I am not sure how to go about this. Rank function places missing values at
the end by default thus skewing the rank relationship between two vectors:
Example:
R : Copyright 2003, The R Foundation for Statistical Computing
Version 1.8.1 (2003-11-21),
2007 Feb 22
0
Error in solve.default
I am trying to run the following function (a hierarchical bayes linear
model) and receive the error in solve.default. The function was
originally written for an older version of SPlus. Can anyone give me some
insights into where the problem is?
Thanks
R 2.4.1 on MAC OSX 2mb ram
Mark Grant
markg at uic.edu
> attach(Aspirin.frame)
> hblm(Diff ~ 1, s = SE)
Error in solve.default(R, rinv)
2004 Mar 03
1
cor(..., method="spearman") or cor(..., method="kendall") (PR#6641)
Dear R maintainers,
R is great. Now that I have that out of the way, I believe I have
encountered a bug, or at least an inconsistency, in how Spearman and
Kendall rank correlations are handled. Specifically, cor() and
cor.test() do not produce the same answer when the data contain NAs.
cor() treats the NAs as data, while cor.test() eliminates them. The
option
use="complete.obs" has
2018 Jan 05
0
Calculating the correlations of nested random effects in lme4
I postulate the following model
AC <- glmer(Accuracy ~ RT*Group + (1+RT|Group:subject) +
(1+RT|Group:Trial), data = da, family = binomial, verbose = T)
Here I predict Accuracy from RT, Group (which has values 0 or 1) and the
interaction of Group and RT (those are the fixed effects). I also estimate
the random effects for both intercepts and slopes for subjects and
different trials.
2004 Oct 22
1
cor, cov, method "pairwise.complete.obs"
Hi UseRs,
I don't want to die beeing idiot...
I dont understand the different results between:
cor() and cov2cov(cov()).
See this little example:
> x=matrix(c(0.5,0.2,0.3,0.1,0.4,NA,0.7,0.2,0.6,0.1,0.4,0.9),ncol=3)
> cov2cor(cov(x,use="pairwise.complete.obs"))
[,1] [,2] [,3]
[1,] 1.0000000 0.4653400 -0.1159542
[2,] 0.4653400 1.0000000
2004 Aug 30
1
Wrong result with cor(x, y, method="spearman", use="complete.obs") with NA's???
Hallo!
Is there an error in cor to calculate Spearman
correlation with cor if there are NA's? cor.test gives
the correct result. At least there is a difference.
Or am I doing something wrong???
Does anybody know something about this?
a<-c(2,4,3,NA)
b<-c(4,1,2,3)
cor(a, b, method="spearman", use="complete.obs")
# -0.9819805
cor.test(a, b,
2004 Jul 09
1
cor.test p-value ties
R:
I got a warning message when running the cor.test function using both
Spearman and Kendall rank correlations saying that the p-value may be
incorrect due to ties in the data. My data has 35 obs and one series has
6 pairs of ties. Does anyone know if this would likely have a great
effect on the p-values calculated.. The values look good; tau = -0.68
with p-value = 8e-9 and rho = =0.84
2010 May 10
1
Problems executing cor(dataset) function in R 2.11.0 for OS X ( It works fine in R 2.10.1)
Dear all,
when trying to replicate John M. Quick's example for correlations between multiple variables posted on:
http://rtutorialseries.blogspot.com/2009/11/r-tutorial-series-zero-order.html
with R 2.11.0 (GUI 1.33) using my MacBook Pro with OX X 10.5.8 I got the following error message
> datavar<-read.csv("dataset_readingTests.csv")
> cor(datavar)
Error in cor(datavar)
2009 Jul 07
1
cor vs cor.test
Hi,
I am trying to use R for some survey analysis, and need to compute the
significance of some correlations. I read the man pages for cor and
cor.test, but I am confused about
- whether these functions are intended to work the same way
- about how these functions handle NA values
- whether cor.test supports 'use = complete.obs'.
Some example output may explain why I am confused:
2013 Mar 29
1
pairs(X,Y) analog of cor(X,Y)?
With a data frame containing some X & Y variables I can get the between
set correlations
with cor(X,Y):
> cor(NLSY[,1:2], NLSY[3:6])
antisoc hyperact income educ
math 0.043381307 -0.07581733 0.25487753 0.2876875
read -0.003735785 -0.07555683 0.09114299 0.1884101
Is there somewhere an analog of pairs(X,Y) that will produce the pairwise
plots of each X against each
2001 Nov 01
1
cor.test for a correlation matrix
Is there a simple way to run cor.test on for a matrix of correlations?
Of course, cor on a data frame produces a correlation matrix, but cor.test will only take two variables at a time. Is there a way to get behavior similar to that of cor with cor.test?
I suppose the programming alternative would be to run two for loops with the number of items and cor test embedded accessing the columns of
2008 Mar 30
2
Problem: using cor.test with by( )
Hello everyone,
I'm a new R user switching from SAS and JMP. In the first few days, I have
been trying to do a fairly simple task but yet found no success. I've
checked the help archive as well as few R textbooks but didn't seem to find
the answer. So, please help me if you can.
Basically, I want to calculate the correlation between variable A and B for
every subject in my