similar to: inconsistency with cor() - "x must be numeric"

Howdy, I have read that if you put a URL in the text of a plot being saved into pdf, the result is a functional hyperlink. I am interested in having text in a plot that is linked to a URL, but I would like the text to be something other than the URL. Is this possible? Thank you. - Fincher

Howdy, I am trying to make a simple monochrome heatmap from 1 row of data. Essentially, I just want a long bar where black represents the max value in the data, white is the minimum, and all values in between are interpolated appropriately. I have tried using heatmap and heatmap.2, but both have issues. heatmap seems to be restricted to only drawing a square plot, and this data requires a

Howdy, This should be simple, but I am finding that I can't find a simple solution. I have a plot to which I am manually adding the annotations to the y-axis with this command: axis(2, c(-4,-3,-2,-1,0,1,2,3,4,5,6,7),labels=c(-4,-3,-2,-1,0,1,2,3,4,5,6,7),cex.axis=8) The issue is that, apparently, R doesn't think that the -1 can fit, even though there is most certainly enough space.

Howdy, I have done many searches and can't seem to find a way around this. I am reading in a .csv file where each row is a dataset and each column represents a position. The values are sparse (there are 2003 positions but usually only 100-200 values) and the idea is to be able to plot each dataset (row) and overlay them in different combinations. What I would like to do is have a plot

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",

I have two datasets that I would like to plot in a single figure. The first plot is generated by a function that then takes a subset of the data. (It is biological data so it is usually by chromosome e.g. function(data1,subset="chr8") ) Since not only are the chromosomes different sizes, but across different datasets there may be different numbers of points for a single chromosome, I

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

Dear R developers: There is a possible bug in calculating the p-value for Spearman's rank correlation. Line 155 in file R-patched/src/library/stats/R/cor.test.R is as.double(round(q) + lower.tail), I think, it should be as.double(round(q) + 2*lower.tail), The reason is that round(q) is expected to be an even number (the S statistic), so the next feasible value is round(q)+2.

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:

Hello, I'm trying to do cor(x1,x2) and I get the following error: Error in cor.default(x1, x2) : missing observations in cov/cor A few things: 1. I've used cor() many times and have never encountered this error. 2. length(x1) = length(x2) 3. is.numeric(x1) = is.numeric(x2) = TRUE 4. which(is.na(x1)) = which(is.na(x2)) = integer(0) {the same goes for is.nan()} 5. I also try

Hello, I am trying to make a correlation matrix in R using cor() and also to get the p-value for each correlation using cor.test(). I can't get these commands to work. I'm getting errors like the following: cor(Pollution, Wet.days) Error in inherits(x, "data.frame") : Object "Wet.days" not found cor("Pollution", "Wet.days") Error in

Using Windows System, R 2.1.0 d is a data frame, 48 rows, 10 columns cor(d) works properly providing all pairwise Pearson correlation coefficients among columns cor.test(d) gives error message "Error in cor.test.default(d) : argument "y" is missing, with no default" Why? Thanks, MCG

Hi, Is there a simple way to do correlation coefficient tests with "cor.test" like I would do with "cor" function? I have a data frame where each column is a list. ================================================ y <- data.frame(a=sample(30, 20), b=sample(30, 20), c=sample(30,20)) cor(y) ================================================ But, cor.test does not take y

Full_Name: Paul Bailey Version: 2.1.1 OS: OS X 10.3 Submission from: (NULL) (68.252.250.144) ?cor [tells me that it has a na.rm variable] > cor(frame2[1,],frame2[2,],na.rm=T) Error in cor(frame2[1, ], frame2[2, ], na.rm = T) : unused argument(s) (na.rm ...) hmm.

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,

Dear all, how can I check the source code for a hidden function like cor.test()? At the moment I get ... > cor.test function (x, ...) UseMethod("cor.test") <environment: namespace:stats> Thanks in advance, Will

Hello, I have a big dataframe with *NO* na's (9 columns, 293380 rows). # doing memory.limit(size = 1000000000) cor(x) #gives Error in cor(x) : missing observations in cov/cor In addition: Warning message: NAs introduced by coercion #I found the obvious workaround: COR <- matrix(rep(0, 81),9,9) for (i in 1:9) for (j in 1:9) {if (i>j) COR[i,j] <- cor (x[,i],x[,j])} #which works fine,

In using cor(data.frame), it is annoying that you have to explicitly filter out non-numeric columns, and when you don't, the error message is misleading: > cor(iris) Error in cor(iris) : missing observations in cov/cor In addition: Warning message: In cor(iris) : NAs introduced by coercion It would be nicer if stats:::cor() did the equivalent *itself* of the following for a data.frame:

Hi I'm computing the correlation between two time-series x_t and y_t-1 (time-series lagged using the lag(y,-1) function) using the cor() function and the returned value is different from the value of ccf() function at the same lag. Any ideas why this is so? Thanks in advance for any hints. Mihnea [[alternative HTML version deleted]]

Dear R-helpers, I'm fighting with the following problem : I want to do bootstrapping on a Kendall correlation with the following code : > cor.function <- function(data,i) cor(data[i, 1], data[i, 2],method="kendall") > boot.ci <- boot.ci(boot.cor <- boot(cbind(x,y),cor.function, R=1000),conf=c(0.95,0.99)) However, I've got problems because I've got ties