similar to: bootstrapped correlation confint lower than -1 ?

Hi, A following function was kindly provided by GGally?s maintainer, Barret Schloerke. function(data, mapping, ...) { p <- ggplot(data = data, mapping = mapping) + geom_point(color = I("blue")) + geom_smooth(method = "lm", color = I("black"), ...) + theme_blank() + theme(panel.border=element_rect(fill=NA, linetype =

Hello R users! I began with R and I must say that it is really nice. I have data with a lot of variables and have a problem to extract the pattern from correlation matrix. So I tried with plotcorr and it went fine. While I was reading the help page of this function, I found that ellipse display can be even better with use of different colors (the code is bellow). However I have a problem to

I am in need of someone's help in correlating gene expression. I'm somewhat new to R, and can't seem to find anyone local to help me with what I think is a simple problem. I need to obtain pearson and spearman correlation coefficients, and corresponding p-values for all of the genes in my dataset that correlate to one specific gene of interest. I'm working with mouse Affymetrix

Hi, I would like to obtain correlation parameters (e.g., coefficients, p-value) for multiple samples in regard to a reference. I have my data in a table with the reference as the second row (first row are headers) and then each sample in a row. What I do so far is load up the data, get the reference sample and use "apply" and "lm" to do the regression: x <-

Hi, I am a newbie of R, and playing with the "ifelse" statement. I have the following codes: ## first, for(i in 1:3) { for(j in 2:4) { cor.temp <- cor(iris.allnum[,i], iris.allnum[,j]) if(i==1 & j==2) corr.iris <- cor.temp else corr.iris <- c(corr.iris, cor.temp) } } this code is working fine. I also tried to perform the same thing in another way with "ifelse":

Hi all, I have a function rho.f which gives a list of estimators. I have the following problems. rho.f(0.3) gives me the right answer. However, if I use rho.f(corr[4]) give me a different answer, even though corr[4]==0.3. This prevents me from using a for loop. Can someone give me some help? Thank you very much in advance. Hannah >

hi everyone, Suppose I have three variables a, b, and c each with 10 values. Now I construct a corr matrix for them. Now I want to give the names of columns of corr matrix as a, b, c, i.e. the first column of corr matrix will have name as ‘a’ second column with ‘b’ and so on. Can anyone give me any code by which I can automatically assign the names of columns of corr matrix which are

I have two variables, minutereturnsa which can be thought of as my independent variable and minutereturnsb which can be thought of as my dependent variable. When I run correlations on the two variables, depending on which of the three methods I use, I get values of between -.15 through -.19. Then, when I do a regression, I get an rsquared of .004 which is more in line with my intuition. In other

I feel like a complete dolt, as I know this question has been asked by others on a fairly regular basis, but I'm going in circles trying to get the following to work: id.prob<-function (tt) { library(mvtnorm) #============================ Makeham<-function(tt) { a2=0.030386513 a3=0.006688287 b3=0.039047537 t<-tt-20 h.t<-a2+a3*exp(b3*t) S.t<-exp(-a2*t+a3/b3*(1-exp(b3*t)))

Hello R users, I am trying to calculate the stochastic lambda for a published matrix population model using the popbio package. Unfortunately, I have been unable to match the published results. Can anyone tell me whether this is due to slightly different methods being used, or have I gone wrong somewhere in my code? Could the answer be as simple as comparing deterministic lambdas to

Hi all, I'd like to use the Hmisc::summarize function, but it uses a function (FUN) of a single vector argument to create the statistical summaries. Consider an easy case: I'd like to compute the correlation between two variables in my dataframe, grouped according to other variables in the same dataframe. For exemple, consider the following dataframe D: V1 V2 V3 A 1 -1 A 1

Two friend reported me a problem, which I can't solve: (I run R-1.0.0, Debian Linux) They hava a function "corr.matrix" (see end of mail), and when they create a 173x173 matrix with this function V <- corr.matrix(0.3, n=173) V1 <- qr.solve(V) reports: Error in qr(a, tol = tol) : NA/NaN/Inf in foreign function call (arg 1) For n < 173, qr.solve returns the correct

Hi, can anyone help me with the following code? Thanks! library(mvtnorm) f2 <- function(n, rho) { var <- matrix(c(1,rho,rho,1), nrow=2, ncol=2, byrow=T) beta <- seq(0, 1, length.out=n+1) alpha <- sort (sapply(1-beta, qnorm)) x <- array(0, dim=c(n, n)) for (s in 1:n) { for (t in 1:n){ if (s>=t) x[s,t] <- pmvnorm(lower=c(alpha[s],

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

I have two binary files(rasters) with the same dimensions. The first file is called `over` and the second is `corr`. I want to replace values in `over` by `NA` whenever `corr` is greater than 0.5. to read the two files we can use: conne <- file("C:corr.bin","rb") over <- readBin(conne, numeric(), size=4, n=1440*720, signed=TRUE) frf <-

Dear all, I want to find the optimal values of a vector, x (with 6 elements) say, satisfying the following conditions: 1. for all x>=0 2. sum(x)=1 3. x[5]<=0.5 and x[6]<=0.5 For the minimisation I'm using nlminb and to satisfy the first 2 conditions the logistic transformation is used with box constraints for condition 3. However, I don't seem to be able to get the values x

Hi, I defined corr to be a function, not realising that this was also the name for correlation in package=boot. How do I explicitly call the corr function within package boot (so, scope up over the current frame, I guess is another way of saying it) without removing my new corr function ? Thanks, Tolga Please follow the attached hyperlink to an important disclaimer

Dear colleagues, What did I not understand ? ->my intention I want to create a new variable: In plain language: If someone is taking anithypertensive treatment (med.hyper==1) table(med.hyper) med.hyper 0 1 472 97 I want to subtract 5 mmHg (rr.dia.2m-5) from the measured diastolic blood pressure (rr.dia.2m) if not treated - the value of the measured diastolic blood pressure should

I just started to write tiny functions and therefore I appologise in advance if I am asking stupid question. I wrote a tiny function to give me back from the original matrix, a matrix showing only the values smaller -0.8 and bigger 0.8. y<-c(0.1,0.2,0.3,-0.8,-0.4,0.9) x<-c(0.5,0.3,0.9,-0.9,-0.7,0.3) XY<-rbind(x,y) extract.values<-function (x) { if(x>=0.8|x<=-0.8)x

Hello, While learning how to manipulate data with R, I found one example that I could not understand. In the following example, the function definition of "maxcor" has an argument named "i" and I don't understand why. Could someone explain why the maxcor function definition needs to have this argument? maxcor = function(i, n = 10, m = 5) { mat =