similar to: cor.test for a correlation matrix

I have to admit that I'm at a bit of a loss here; any pointers would be greatly appreciated. I've been making correlation matricies from some of my datasets, and have been instructed to get the probability values for each of these correlations. I've checked the online help for info on both the cor and cov functions, but I was unable to find any relevant info on finding how to obtain

Dear all, Sorry for the simplicity of the question, but how does one go about removing duplicated rows in a data.frame? I'm looking for a quick and simple solution, as my data.frames are relatively large (50000 by 50). I've racked my brain and searched the help files and found nothing useful or quick, only duplicated() and unique() which work only work on lists. Thanks Gary.

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

Full_Name: Glenn Stone Version: 1.5.1 and 1.6.0 OS: win2000 Submission from: (NULL) (168.140.227.9) The following code produces incorrect fitted values in version 1.5.1 and an error in 1.6.0 Error in "contrasts<-"(*tmp*, value = "contr.treatment") : contrasts apply only to factors In addition: Warning message: variable ihalf is not a factor in:

Hi R-users, I have a simple question for R heavy users. If I have a data frame like this dfr <- data.frame(id=1:16, categ=rep(LETTERS[1:4], 4), var3=c(8,7,6,6,5,4,5,4,3,4,3,2,3,2,1,1)) dfr <- dfr[order(dfr$categ),] and I want to score values or points in variable named "var3" following this kind of logic: 1. the highest value of var3 within category (variable named

Hi, I encountered a booting problem with memdisk 2.83, USB and IBM Thinkpad T61, apparently the same issue as described here: http://syslinux.zytor.com/archives/2008-April/009850.html The boot process always stops after "Loading boot sector... booting...". With debug tracers enabled, the last few output lines are: Loading boot sector... FR<p>Dbooting...

dear professor: thank you for your help,witn your help i develop the nomogram successfully. after that i want to do the internal validation to the model.i ues the bootpred to do it,and then i encounter problem again,just like that.(´íÎóÓÚerror to :complete.cases(x, y, wt) : ²»ÊÇËùÓеIJÎÊý¶¼Ò»Ñù³¤(the length of the augment was different)) i hope you tell me where is the mistake,and maybe i have

Hello, I think this is a simple problem but I am not coming up with a simple solution. I think it just an indexing problem. I can easily replace values in a matrix from a dataframe when the dataframe has row and column numbers. In the example below I use row and column names and I can not get it to work #make a matrix where rows and columns are the lat and long for a bounding box of Australia

A loose idea for *post*-0.50 development I've been giving a some (but not all that many) thoughts to whether some of the conceptual difficulties facing newcomers could be avoided by having simplified functions for common operations. We already have parts of this, e.g. in Kurts ctest routines. Specifically, I was thinking about data frames: How about

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

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

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

I would be incredibly grateful to anyone who'll help me translate some SAS code into R code. Say for example that I have a dataset named "dat1" that includes five variables: wshed, site, species, bda, and sla. I can calculate with the following SAS code the mean, CV, se, and number of observations of "bda" and "sla" for each combination of

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

dear professor: I have a problem about the nomogram.I have got the result through analysing the dataset "exp2.sav" through multinominal logistic regression by SPSS 17.0. and I want to deveop the nomogram through R-Projject,just like this : > n<-100 > set.seed(10) > T.Grade<-factor(0:3,labels=c("G0", "G1", "G2","G3")) >

Hi R-users, How do I calculate a number of NA's in a row of every second column in my data frame? As a starting point: dfr <- data.frame(sapply(x, function(x) sample(0:x, 6, replace = TRUE))) dfr[dfr==0] <- NA So, I would like to count the number of NA in row one, two, three etc. of columns X1, X3, X5 etc. Thanks in advance Lauri [[alternative HTML version deleted]]

Hi all: Can someone advice me on how to hold the residuals Mean sq value on a string so it can be used in other calculations. I was trying something like this: Msquare<-dfr$Mean sq but fails..Thanks dfr <- read.table(textConnection("percentQ Efficiency 1.565 0.0125 1.94 0.0213 0.876 0.003736 1.027 0.006 1.536 0.0148 1.536 0.0162 2.607 0.02 1.456 0.0157 2.16 0.0103

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:

Dear useRs, I have a data frame and I want to plot all rows. Each row is represented as a line that links the values in each column. The plot looks like this: dfr <- data.frame(A=sample(1:50,10),B=sample(1:50,10), C=sample(1:50,10),D=sample(1:50,10)) xa <- 10*1:4 plot(c(10,40),c(0,50)) for (i in 1:nrow(dfr)) { lines(xa,dfr[i,],pch=20,type="o") } Things get more complicated

Dear r-users, Suppose I have three datasets: Dataset-1: Date x y Jan-1,2005 120 230 Jan-2,2005 123 -125 Jan-3,2005 -110 300 Jan-4,2005 114 -21 Jan-7,2005 11 299 Mar-5,2005 200 311 Dataset-2: Date x y Jan-2,2005 123 -125 Jan-3,2005 -110 300 Jan-4,2005 114 -21