similar to: How to avoid this warning message

Hi friends, Any idea why do i get this warning?And also why all computed p-values are NaN. Have shown below what i did in Windows r-console.:-- > df c1 c2 1 1 50 2 NA NA 3 4 NA 4 7 6 5 NA 7 6 10 10 > r<-cor(x=df,y=NULL,use="complete.obs",method=c("pearson")) > r c1 c2 c1 1.0000000 -0.9148074 c2 -0.9148074 1.0000000 > cor.p.values<-

Not too hard to fix, the following buglet (new in 1.3.0), but I'm about to leave for one week (of vacation).. Here is an example (for Linux) : lynne{sfs}214> cd /tmp lynne{sfs}215> mkdir blue lynne{sfs}216> cd blue /tmp/blue lynne{sfs}217> echo 'data(package = "mva")'|R-1.3.0 --vanilla R : Copyright 2001, The R Development Core Team Version 1.3.0

can you recommend a good manual for R that starts with a data set and gives demonstrations on what can be done using R? I downloadedR Langauage definition and An introduction to R but haven't found them overly useful. I'd really like to be able to follow some tutorials using a dataset or many datasets. The datasets I have available on R are Data sets in package 'datasets':

I would like to turn off the warnings from cor.test while retaining exact=NULL. Is that possible ? > cor.test(c(1,2,3,3,4,5), c(1,2,3,3,4,5), method = "spearman") Spearman's rank correlation rho data: c(1, 2, 3, 3, 4, 5) and c(1, 2, 3, 3, 4, 5) S = 0, p-value < 2.2e-16 alternative hypothesis: true rho is not equal to 0 sample estimates: rho 1 Warning message: In

>>>>> Ben Bolker <bbolker at gmail.com> >>>>> on Fri, 15 Jul 2016 16:45:50 -0400 writes: > I'm sorry I haven't boiled this down to a more-minimal example yet, > but ... > I'm working on an S3 method (tidy.merMod, in the 'broom' package). It > normally handles 'merMod' objects from the lme4 package,

Dear R-help, Can anyone explain the meaning of the warning, Singular precision matrix in level -1, block 1 ? Or how to track down where it comes from? More precisely, using the nlme package, I'm issued with the warning itt2 <- lme(lrna~rx.nrti+lbrna, random=~1|patid, cor=corExp(form=~days|patid,nugget=T), weights=varPower( form=~lbrna),data=rna3) Warning messages: 1: Singular

Dear R-users: I am runing R 1.6.2 with Windows XP. I try to calculate Pearson correlation and Spearman correlation of any pairwise columns of 8000 x 80 data matrix with missing values and randomize the matix 1000 times and calculate this two correlations again. The code bellow for Pearson is working fine but for Spearman got the error bellow for randomized data matrix and R console is stop

Hello, Sorry if this is somewhere in the archives but i couldn't find it. I am using the funtion cor() and inputting a large matrix with a column of 0, for which i get NA's for. I'm looking for a way to overcome that divide by 0 error btw but my real issue is this: I specify the method as pearson but the error messages always say kendall ex) > read.csv("ncatest.csv",

Hello everyone, Could you please help me find out if R supports matrixes inside matrixes? This is what I would like to do I have an area map of humidity per km. I would like at every cell to keep also information about the height of this area, the current temperature etc. Is something like that supported? I would like to thank you in advance for your help Best Regards Alex

Dear R Users, I was hoping for some help with a recurrent error message in lmer. I am trying to model the effect of temperature on metabolic rate in animals (response = int.length) at different temperatures (mean.sst), with repeated measurements on the same individuals (random effect = female). Ideally I would make a random slope and intercept model where the rate can change differently with

Odd behaviour of function cor() in R-2.10.1-64bit-Unix In a dataset with 1366 patients and 244 clinical variables Spearman's Rho was calculated for some fatty acids and BMI and came over something rather odd: R seems to calculate Rho differently on 2.10.1-64bit-Unix and 2.9.0-32bit-Windows when I calculate the complete (244x244) correlation matrix and then pick out the values I am

>From a somewhat ill-designed education experiment, I have categorical data with two between subject variables and one within subject variable. Since it is categorical (essentially counts of answer choices on multiple choice questions), I'm looking for some chi-squared method. I know how to generalize Pearson's chi-square for n between subject dimensions, and I know McNemar's test

Hi, This is Kotien Wu from NIH/NCI. We want to use R function for our web: http://cgap.nci.nih.gov It works for functions in R/R-1.9.1/src/nmath/standalone very well. We have function GetPvalueForT.c which has #define MATHLIB_STANDALONE 1 #include <Rmath.h> double GetPvalueForT ( double t, double deg ) { return 2 * pt(t, deg, 0, 0); } We create GetPvalueForT.i, which has /* File :

I' ve seen that several people are looking for a function that creates a barplot with an error indicators (I was one of them myself). Maybe you will find the following code helpful (There are some examples how to use it at the end): # Creates a barplot. #bar.plot() needs a datavector for the height of bars and a error #indicator for the interval #many of the usual R parameters can be set:

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 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, Following the Writing R Extensions manual, I created a method for the cor function. As cor is not a generic, I followed the advice of section 6.1 of the same manual and did the following: cor <- function(x, ...) UseMethod("cor") cor.default <- stats::cor cor.symcoca <- function{ some code } I used package.skeleton to create the basic set-up of my package, containing the

Hi R users, I generated a square correlation matrix for the dat dataframe below; dat<-data.frame(g1=c(1,0,0,1,1,1,0,0,0), g2=c(0,1,0,1,0,1,1,0,0), g3=c(1,1,0,0,0,1,0,0,0), g4=c(0,1,0,1,1,1,1,1,0)) library("Hmisc") dat.rcorr = rcorr(as.matrix(dat)) dat.r <-round(dat.rcorr$r,2) however, I want to modify this correlation calculation;

Hello I am a new user of R . and I ve problem with R and netcdf . I succed installation , I could use all examples . But when I take my netcf it is different . I want to do statistic on this kind of file . 1) first calculate mean . my data is like that through ncdump -h test.nc netcdf test { dimensions: lat = 301 ; lon = 401 ; time = UNLIMITED ; // (80 currently)

Full_Name: thomas cornulier Version: 1.9.0 and 1.9.1 OS: Win XP Submission from: (NULL) (194.254.155.62) the following function produces R crashes under windows XP platform i386-pc-mingw32 arch i386 os mingw32 system i386, mingw32 status major 1 minor 9.1 year 2004 month 06 day