similar to: Turning off warnings from cor.test

Displaying 20 results from an estimated 10000 matches similar to: "Turning off warnings from cor.test"

2003 Oct 22
6
Something strange in cor.test in R-1.8.0 (PR#4718)
Full_Name: Ian Wilson Version: R-1.8.0 OS: Windows (but own compilation) Submission from: (NULL) (139.133.7.38) the p-value is incorrect for cor.test using method "spearman" in R-1.8.0. This was not the case in R-1.7.1. Version R-1.8.0 on Windows > cor.test(rnorm(50),rnorm(50),method="spearman") Spearman's rank correlation rho data: rnorm(50) and rnorm(50) S
2009 Nov 30
1
cor.test(method = spearman, exact = TRUE) not exact (PR#14095)
Full_Name: David Simcha Version: 2.10 OS: Windows XP Home Submission from: (NULL) (173.3.208.5) > a <- c(1:10) > b <- c(1:10) > cor.test(a, b, method = "spearman", alternative = "greater", exact = TRUE) Spearman's rank correlation rho data: a and b S = 0, p-value < 2.2e-16 alternative hypothesis: true rho is greater than 0 sample estimates:
2010 Jun 08
2
cor.test() -- how to get the value of a coefficient
Hi, all. Yet another beginner to R : ) I wonder, how it's possible to get the value of a coefficient from the object produced by cor.test() ? > cor.test(a, b, method="spearman") Spearman's rank correlation rho data: a and b S = 21554.28, p-value = 2.496e-11 alternative hypothesis: true rho is not equal to 0 sample estimates: rho 0.6807955 Warning message: In
2003 Nov 07
2
Bug in cor.test - Spearman
Greetings. There seems to be a problem with the P-value computation in the cor.test with method="spearman". In R1.8.0 (MS Windows) I seem to be getting intermittently nonsense P-values, but the rho's are OK. I can get this reproducibly with the toy example attached where the first use is OK and subsequent calls with the same data give nonsense. (I have also seen the problem
2004 Mar 19
1
cor.test() -> p-values may be incorrect due to tie
Hi R specialists, When testing the association between two time series the cor.test gives the following message...-> p-values may be incorrect due to tie What does it mean? (it is not described in the help) Thankx, Jan > cor.test(Origi[,1],Origi[,2], alternative = c("two.sided"),method = c("spearman"), conf.level = 0.95) Spearman's rank correlation rho
2010 Jun 09
1
bug? in stats::cor for use=complete.obs with NAs
Arrrrr, I think I've found a bug in the behavior of the stats::cor function when NAs are present, but in case I'm missing something, could you look over this example and let me know what you think: > a = c(1,3,NA,1,2) > b = c(1,2,1,1,4) > cor(a,b,method="spearman", use="complete.obs") [1] 0.8164966 > cor(a,b,method="spearman",
2008 Jun 19
3
how to extract object from stats test output (cor.test)?
Hello, Is there a way to extract output objects from a stats test without viewing the entire output? I am trying to do so in the following: define a vector of length j for( i in 1: length (vector)) { vector[i] = cor.test (datavector1, datavector2[i], method=("spearman")) } I would like the reported Spearman's rho to be saved in a vector. I have tried a few different ways of
2006 Sep 13
1
S in cor.test(..., method="spearman")
Dear HelpeRs, I have some data: "ice" <- structure(c(0.386, 0.374, 0.393, 0.425, 0.406, 0.344, 0.327, 0.288, 0.269, 0.256, 0.286, 0.298, 0.329, 0.318, 0.381, 0.381, 0.47, 0.443, 0.386, 0.342, 0.319, 0.307, 0.284, 0.326, 0.309, 0.359, 0.376, 0.416, 0.437, 0.548, 41, 56, 63, 68, 69, 65, 61, 47, 32, 24, 28, 26, 32, 40, 55, 63, 72, 72, 67, 60, 44, 40, 32, 27, 28, 33,
2006 Dec 05
1
Spearman correlation ties and discrepancies
Hi. I am currently trying to run some Spearman correlations, and have encountered two issues. 1) When using cor.test() with a variable that includes ties, I get the "Cannot compute exact p-values with ties" error. I have read that this function now uses an asymptotic formula that allows for ties, so do not understand why I am getting this error. (I am running version 2.4.0.) I
2004 Mar 15
1
spearman rank correlation problem
Hello R gurus, I want to calculate the Spearman rho between two ranked lists. I am getting results with cor.test that differ in comparison to my own spearman function: > my.spearman function(l1, l2) { if(length(l1) != length(l2)) stop("lists must have same length") r1 <- rank(l1) r2 <- rank(l2) dsq <- sapply(r1-r2,function(x) x^2) 1 - ((6 * sum(dsq))
2004 May 20
1
Spearman probabilities and SuppDists
cor.test and SuppDists give me different P-values for the same Spearman's rho. Which is correct, or am I doing something wrong? > x <- c(44.4, 45.9, 41.9, 53.3, 44.7, 44.1, 50.7, 45.2, 60.1) > y <- c( 2.6, 3.1, 2.5, 5.0, 3.6, 4.0, 5.2, 2.8, 3.8) > cor.test(x,y,method="spearman") Spearman's rank correlation rho data: x and y S = 48, p-value =
2009 Aug 16
2
bootstrapped correlation confint lower than -1 ?
Dear R users, Does the results below make any sense? Can the the interval of the correlation coefficient be between *-1.0185* and -0.8265 at 95% confidence level? Liviu > library(boot) > data(mtcars) > with(mtcars, cor.test(mpg, wt, met="spearman")) Spearman's rank correlation rho data: mpg and wt S = 10292, p-value = 1.488e-11 alternative hypothesis: true rho is not
2011 Aug 09
1
Correlation Matrix - p value?
Hello all, I've run a Spearman's Rank test to discern relationships between landscape characteristics and a specific aspect of river behaviour. I've executed a correlation matrix between the one dependent variable and all of the predictors, which gives me a nice output of Spearman's Rho values. However, I also need to somehow find the "p" value, to assess the strength
2010 Feb 08
2
Incorrect Kendall's tau for ordered variables (PR#14207)
Full_Name: Marek Ancukiewicz Version: 2.10.1 OS: Linux Submission from: (NULL) (74.0.49.2) Both cor() and cor.test() incorrectly handle ordered variables with method="kendall", cor() incorrectly handles ordered variables for method="spearman" (method="person" always works correctly, while method="spearman" works for cor.test, but not for cor()). In
2011 Nov 01
1
How to interpret Spearman Correlation
Hi, I am not really familiar with Correlation foundations, although I read a lot. So maybe if someone kindly help me to interpret the following results. I had the following R commands: correlation <-cor( vector_CitationProximity , vector_Impact, method = "spearman", use="na.or.complete") cor_test<-cor.test(vector_CitationProximity, vector_Impact,
2007 Dec 04
1
R-help
> I recently picked up R for econometrics modeling, and I am confronted with a > problem. I use cor.test() for spearman test, and want to get the "rho" and > "P-value" in the summary. Would you please tell me how to get them? Thank you very much! > > > > Here is the cor.test() summary: > > Spearman's rank correlation rho > > > > data:
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
2007 Dec 04
1
How can I use the rho value in the cor.test() summary?
I want to give the "rho" value below to another variable.How ? > Spearman's rank correlation rho > > > > data: a[, 3] and a[, 2] > > S = 22, p-value = 0.001174 > > alternative hypothesis: true rho is not equal to 0 > > sample estimates: > > rho > > 0.8666667 -- View this message in context:
2005 Oct 24
2
Spearman's Rho Help!
Hi, I have a dataset with four categories of data, the number of samples are not the same in each category. I want to find the Spearaman's Rho. Let me give an example. x=(14.22770439,26.49420624,46.7277932,19.02550707,23.37379361,16.97789862,19.77100085,23.11270162,13.72929843,33.54430621,14.4756979,70.15811106,11.22789833,NA,NA,NA)
2008 Jan 02
2
strange behavior of cor() with pairwise.complete.obs
Hi all, I'm not quite sure if this is a feature or a bug or if I just fail to understand the documentation: If I use cor() with pairwise.complete.obs and method=pearson, the result is a scalar: ->cor(c(1,2,3),c(3,4,6),use="pairwise.complete.obs",method="pearson") [1] 0.9819805 The documentation says that " '"pairwise.complete.obs"' only