similar to: bootstrapping a matrix and calculating Pearson's correlation coefficient

Hi, I'm currently trying to find/define a relationship between one dependent and several independant variables. The problem is that i cannot use the normal multiple regression/correlation in Spss because the data is not normal distributed. i calculated the spearman roh and Kendalls tau Correlation and also some partial correlations in R. Now i wanna find out the the multiple correlation

Dear R-Helpers, I am trying to bootstrap the coefficient of variation on a suite of vectors, here I provide an example using one of the vectors in my study. When I ran this script with the vector x <-c(0.625, 0.071428571, 0.133333333, 0.125, 0), it returned CV(boot) [the second one], and stderr(boot) [the second one] without problem. However, when I ran it with the vector in the

I run the following code: library(rpart) data(kyphosis) fit <- rpart(Kyphosis ~ ., data=kyphosis) plot(fit) text(fit, use.n=TRUE) The text labels represent the count of each class at the leaf node. Unfortunately, the numbers are rounded and in scientific notation rather than the exact number of examples sorted by that node in each class. The plot is supposed to look like

Dear All, In a package, I want to use PCA function. The structure I used follow this page: http://www.statmethods.net/advstats/factor.html. fit<-principle(mydata, nfactors=9, rotation=TRUE) or: result<-PCA(mydata) But I don't known why R language in my computer noticed: "not found principle", "not found PCA". I download and installed

Hi R, I was using 'as.dendrogram' with the DIST coefficient, where the smaller values of the DIST coefficient, say that the objects are closer to each other, while the larger values of the coefficient say that the objects are far from each other. But now, I have my coefficient as the DICE coefficient(in some sense similar to correlation coefficient), where the larger coefficient

Dear All, It might be a simple question. But I could not find the answer from function “prcomp” or “princomp”. Does anyone know what are the codes to get coefficient and scores of Principal component analysis in R? Your reply will be appreciated! Best Zunqiu [[alternative HTML version deleted]]

How do I get non-squared correlation coefficient in some more sensible way than sqrt(summary(lm(y~x))$r.squared)? Thanks Matej -- Matej Cepl, matej at ceplovi.cz, Finger: 89EF 4BC6 288A BF43 1BAB 25C3 E09F EF25 D964 84AC 138 Highland Ave. #10, Somerville, Ma 02143, (617) 623-1488 The difference between death and taxes is death doesn't get worse every time Congress meets -- Will

I did a linear correlation of data using glm.fit and stored the output in the object "f": f <- glm.fit(x, y, w) I am intereseted in estimating the quality of the correlation. I am used to do it using pearson correlation coefficient "r" or "r^2". Can I extract this coefficient from the output of glm.fit? Is there another number in the output of glm.fit that

Hello all, I would like to compare the similarity of two cluster solutions using a validation criteria (such as Hubert's gamma coefficient, the Dunn index the corrected rand index and so on) I see (from here:http://www.statmethods.net/advstats/cluster.html) that the function cluster.stats() in the fpc package provides a mechanism for comparing 2 cluster solutions - *BUT* - it requires me to

I ran this code (several times) from the Quick-R web page ( http://www.statmethods.net/advstats/cart.html) but my cross-validation errors increase instead of decrease (same thing happens with an unrelated data set). Why does this happen? Am I doing something wrong? # Classification Tree with rpart library(rpart) # grow tree fit <- rpart(Kyphosis ~ Age + Number + Start,

I am interested in applying a "classification tree" analysis where the response variable is a censored variable (survival data). I've discovered the package 'party' through this page: http://www.statmethods.net/advstats/cart.html. However, as my sample is not very big I would like to apply 'bootstrap' and use 'random forests', but with my censored response

I am trying to create a classification tree using either tree or rpart functions but when it comes to plotting the results the formatting I get is different than what I see in all the tutorials (like http://www.youtube.com/watch?v=9XNhqO1bu0A or http://www.youtube.com/watch?v=m3mLNpeke0I&feature=related or http://www.statmethods.net/advstats/cart.html "tree for kyphosis"). I am

Hi! All, To find co-expressed genes from a expression matrix of dimension (9275 X 569), I used rcorr function from library(Hmisc) to calculate pearson correlation coefficient (PCC) and their corresponding p-values. From the correlation matrix (9275 X 9275) and pvalue matrix (9275 X 9275) obtained using rcorr function, I wanted to select those pairs whose PCC's are above 0.8 cut-off and then

Thanks to Mr.Liviu Androvic and Mr.Richard Rowe helped me in PCA. Because I have just learn R language in a few day so I have many problem. 1) I don't know why PCA rotation function not run although I try many times. Would you please hepl me and explain how to read the PCA map (both of rotated and unrotated) in a concrete example. 2) Where I can find document relate: Plan S(A), S(A*B),

Hi, I am trying to do a Principal component analysis on histogram data. Basically, I have a group of subjects and for each of them, I have a column of bin-counts (vis-a-vis intervals) and a corresponding column of frequencies (or normalized frequencies). The bin counts are the same for all the subjects. I also have a group-averaged histogram (with the same bin counts and a column of frequencies)

Hi, I have seen that R has a implementation of decision trees; however, after I have the tree with the classification: R Quinlan's trivial example of the "golf" decision tree. Outlook Temperature Humidity Windy PlayDontPlay 1 sunny 85 85 false DontPlay 2 sunny 80 90 true DontPlay 3 overcast 83 78 false Play 4 rain 70 96 false Play ... What's next? I mean, what is this

Hi, Suppose I want to compare the results of two clustering methods, what is the best way to do it? Thanks Regards, -k

I have an exercise. With 3 kinds of yohourt a,b,c. There are 25 participatients estimate 3 norms: taste (va,vb,vc), structure (ca,cb,cc) and price (ga,gb,gc) and give the mark from 1 to 5. I don't know how to PCA this data. Please help me! I attached the data file follow: Va Vb Vc Ca Cb Cc Ga Gb Gc 4 2 4 5 5 5 4 4 2 2 2 4 3 2 5 4 5 1 2 2 1 2 3 3 3 1 4 1 1 2 2 3 3 4 3 2 3 4 4 4 3 1 2 1 2 1 1 1

Hi folks, I'm trying to estimate bias-corrected percentile (BCP) confidence intervals on a vector from a simple for loop used for resampling. I am attempting to follow steps in Manly, B. 1998. Randomization, bootstrap and monte carlo methods in biology. 2nd edition., p. 48. PDF of the approach/steps should be available here: https://wyocoopunit.box.com/s/9vm4vgmbx5h7um809bvg6u7wr392v6i9 If

Hi all, Are there functions in R that could help me do the following? We have a special type of regression which is called Geometric Mean Regression. We have done some search and found the following: https://stat.ethz.ch/pipermail/r-help/2011-July/285022.html The question is: how to do the statistical inference on GMR results? More specifically, we are looking for the prediction interval: