similar to: a question about sort and BH

I append below a suggested update for p.adjust(). 1. A new method "yh" for control of FDR is included which is valid for any dependency structure. Reference is Benjamini, Y., and Yekutieli, D. (2001). The control of the false discovery rate in multiple testing under dependency. Annals of Statistics 29, 1165-1188. 2. I've re-named the "fdr" method to "bh" but

The Partek package (www.partek.com) allows only two selections for Multiple Test Correction: Bonferroni and Dunn-Sidak. Can anyone suggest why Partek implemented Dunn-Sidak and not the other methods that R has? Is there any particular advantage to the Dunn-Sidak method? R knows about these methods (in R 2.1.1): > p.adjust.methods [1] "holm" "hochberg" "hommel"

Hello, I am trying to use the p.adjust function for multiple testing. here is what i have 9997 201674_s_at 0.327547396 9998 221013_s_at 0.834211067 9999 221685_s_at 0.185099475 I import them from excel have have the gene symbol as well as the pvalue here is the issue > pa<-p.adjust(pt,method="BH") Error in p[nna] : object is not

Dear List, I have been trying to use p.adjust() to do BH multiple test correction and have gotten some unexpected results. I thought that the equation for this was: pBH = p*n/i where p is the original p value, n is the number of tests and i is the rank of the p value. However when I try and recreate the corrected p from my most significant value it does not match up to the one computed by the

>>>>> "GS" == Gordon K Smyth <smyth@wehi.edu.au> >>>>> on Sat, 8 Jan 2005 01:11:30 +1100 (EST) writes: <.............> GS> p.adjust() unfortunately gives incorrect results when GS> 'p' includes NAs. The results from topTable are GS> correct. topTable() takes care to remove NAs before GS> passing

Hi, There is a question that I am confused. I have a set of data like this: hsa-miR-205--GATA3 0.797882767 1.08E-13 hsa-miR-205--ITGB4 0.750217593 1.85E-11 hsa-miR-187--PGF 0.797604155 3.24E-11 hsa-miR-205--SERPINB5 0.744124886 3.28E-11 hsa-miR-205--PBX1 0.734487224 7.89E-11 hsa-miR-205--MCC 0.72499934 1.80E-10 hsa-miR-205--WNT5B 0.717705259 3.33E-10 hsa-miR-200c--PKN2 0.721746815

http://bugs.freedesktop.org/show_bug.cgi?id=25453 Summary: nouveau + multiple xorg servers + suspend2ram trashes root partition Product: xorg Version: unspecified Platform: x86-64 (AMD64) OS/Version: Linux (All) Status: NEW Severity: critical Priority: high Component: Driver/nouveau

Dear all, in R 3.1.0, this is happening: > cummin(c(1+1i,2-3i,4+5i)) Error in cummin(c(1 + (0+1i), 2 - (0+3i), 4 + (0+5i))) : 'cummax' not defined for complex numbers > cummax(c(1+1i,2-3i,4+5i)) Error in cummax(c(1 + (0+1i), 2 - (0+3i), 4 + (0+5i))) : 'cummin' not defined for complex numbers It may be fixed in R-devel, but I thought I'd mention it to make sure

Dear all, I constructed this function called my.boxplot.stats by replacing fivnum() with quantile() in function boxplot.stats(). So I can try different quantile methods in bwplot(). The problem is I couldn't pass different values to the "type" argument to my.boxplot.stats, which in turn is an argument in bwplot(). Now I just have to manually change the "type" value in

Hi, The function cummax() seems to have a bug. > x <- c(NA, 0) > storage.mode(x) <- "integer" > cummax(x) [1] NA 0 The correct result of this case should be NA NA. The mistake in [ https://github.com/wch/r-source/blob/trunk/src/main/cum.c#L130-L136] may be the reason. Best Regards, Dongcan -- Dongcan Jiang Team of Search Engine & Web Mining School of Electronic

Hello, I know this has been covered on here before, but as a complete novice, I need a little more guidance. I would like to produce boxplots with the whiskers extending to the 10 and 90th percentiles. I found this code: myboxplot.stats <- function (x, coef = NULL, do.conf = TRUE, do.out = TRUE) { nna <- !is.na(x) n <- sum(nna) stats <- quantile(x, c(.1,.25,.5,.75,.9), na.rm

Hi all, I'm just getting started with R and I would appreciate some help. I'm having trouble creating a boxplot with whiskers at the 95th and 5th percentiles instead of at 1.5 * IQR. I have read the relevant documentation, and checked existing mails on this topic. I found a small modification that should work : https://stat.ethz.ch/pipermail/r-help/2001-November/016817.html and tried to

Dear all, It was a pleasure to meet you at Iowa State University. Two days ago I submitted two experimental packages to CRAN (hope it will be there soon): rindex: quick indexing of large objects (currently only character, see ?index) regtest: some first support for automated regression testing (heavily used in \dontshow{} section of ?index) With rindex you can for example i <-

Hi,?are the methods for multiple testing p value adjustment (Shaffer, Westfall, free) implemented in the function adjusted() in multcomp package so called closed testing procedure? what about those methods (holm, hochberg, hommel, BH, BY) implemented in the p.adjust() in the stats package? ? Thanks ? John

Dear R Helpers, I have run into a problem trying to perform a number of actions on a set of quantmod data objects through a loop and I am hoping that this is an easy problem for someone else as opposed to very difficult for me. The example task is to get the first three objects of the quarterly balance sheet for a number of companies from the getFinancials object and put them together into a

Sorry to repost this, but it looks like it's getting buried in r-help (originally posted October 5: my experience says that if it hasn't been answered by then it won't be). I wouldn't bother, but I'm worried that r-devel might be better, *and* a previous e-mail of mine on the subject in January also seemed to get buried. Synopsis: boxplot notches look weird when notches are

Hi everyone, I think I have found a minor issue with the R function "boxplot.stats". But before I make such a rash comment, I'd like to check my facts by fixing what I think is the problem. However, why I try to do this, R does not behave as I expect. Can you tell me what I'm doing wrong? If I use the command: debug(boxplot.stats) I am allowed to step through the code as

Full_Name: Peter Ehlers Version: 1.6.0 OS: Windows 2000 Pro Submission from: (NULL) (136.159.61.178) In: p.adjust package:base R Documentation In the paragraph: Hochberg's and Hommel's methods are valid when the hypothesis tests are independent or when they are non-negatively associated (Sarkar, 1998; Sarker and Chang, 1997). Hommel's method is

Hi! I noticed that cumsum behaves different than the other cumulative functions wrt. NaN values: > values <- c(1,2,NaN,1) > for ( f in c(cumsum, cumprod, cummin, cummax)) print(f(values)) [1] 1 3 NA NA [1] 1 2 NaN NaN [1] 1 1 NaN NaN [1] 1 2 NaN NaN The reason is that cumsum (in cum.c:33) contains an explicit check for ISNAN. Is that intentional? IMHO, ISNA would be better

Hello, I'm dealing with financial time series. I'm trying to find out X in this sentence: The most recent close is the lowest level since X(date). Here's an example of what I'm looking for: library(fBasics) data(DowJones30) tail(DowJones30[,1:5],n=10) I need to come up with a vector that would look like this AA AXP T ... 2000-12-21