search for: pi0

...already been mentioned. If you use a calculation to generate n observations in random number generators and you don't round to the nearest integer you may be generating n-1 numbers not n numbers as you thought depending on the storage precision of the calculation. e.g. > m <- 1000 > pi0 <- 0.9 > length(rnorm(m * (1-pi0))) [1] 99 # Should be 100 > options(digits=16) > m * (1-pi0) [1] 99.99999999999997 > identical(m*(1-pi0), 100) [1] FALSE Random number generation generates the floor of n observations, this feature occurs on R-1.8.1 on linux Redhat8, and winXP (also...

Dear colleagues, This is not strictly a R question, but I hope it is ok to ask on the list. I fed a vector of p-values from about 20 million anova tests to the package q-value and obtained this output: > qsummary(asso_p.qvalue) Call: qvalue(p = asso_p.vec) pi0: 1 Cumulative number of significant calls: <1e-04 <0.001 <0.01 <0.025 <0.05 <0.1 <1 p-value 22711 59067 262103 551316 1013241 1936797 20048103 q-value 3554 5211 9275 12807 16951 24557 20048103 I can see that there are many hits with very s...

I am using storey's qvalue package but I keep on getting errors. Why is this? > qvalue(p, lambda=0.5)$pi0 [1] "ERROR: p-values not in valid range." Error in qvalue(p, lambda = 0.5)$pi0 : $ operator is invalid for atomic vectors -- Thanks, Jim. [[alternative HTML version deleted]]

...range in a xy plot for several plots, instead of specifying them for each plot. The following is my code for generalizing the matrix and draw the histogram. ############gen is the function to generate the dta gen <- function(m, rho) { library(MASS) set.seed(103) theta <- 0 theta1 <- 2 pi0 <- 0.9 mzero <- pi0*m mean <- c(rep(theta, mzero), rep(theta1,m-mzero)) J <- rep(1, m) var <- function(rho) {(1-rho)*diag(m)+ rho*J%*%t(J)} t <- mvrnorm(1, mean, var(rho)) return(t) } ####### w is the matrix. A histgram is drawn for each of the rows. n <...

Dear all, I need to do some calculation where the code used are below. I get error message when I choose k to be large, say greater than 25. The error message is "Error in integrate(temp, lower = 0, upper = 1, k, x, rho, m) : the integral is probably divergent". Can anyone give some help on resolving this. Thanks. Hannah m <- 100 alpha <- 0.05 rho <- 0.1 F0

...the same result as specifying a Q-value in the fdr function itself calculating a false discovery rate threshold alpha level so that FDR<=Q. So it adjusts for all FDR desired levels. If your p-value threhold is 0.05 then the expected proportion of false discoveries is 5%. e.g. n <- 1000 pi0 <- 0.5 x <- rnorm(n, mean=c(rep(0, each=n*pi0), rep(3, each=n - (n*pi0)))) p <- 2*pnorm( -abs(x)) p <- sort(round(p,3)) p.adjusted <- p.adjust(p, method="fdr") # Controlling fdr at Q, and p.adjust at level alpha Qvalue <- alpha <- 0.05 threshold <- fdr(p, Q=Qv...

You asked the same question on the Bioconductor mailing list back in August. At that time, you suggested yourself a solution for how the adjusted p-values should be interpreted. I answered your query and told you that your interpretation was correct. So I'm not sure what more can be said, except that you should read the article Wright (1992), which is cited in the help entry for p.adjust(),

Complains about missing Int16 functionality. So for 64bit on Arm you have to compile without –enable-neon and that has a huge effect on the AEC functionality. The Pi3 with neon is just struggling with the AEC routines as its audibly better on a Pi4 but its not the garble that a Pi0 produces. Without the neon on the Pi3 the 1.2 – 1.85 perf boost of neon with FFT is lost and it really effects AEC effectiveness. There are quite a number of low cost ArmSocs now all approx. Pi3 level and above that really benefit from neon support with FFT. Arm have specific Libs for this https:...

...is a 2 x 3 and 80% pf the tables are true nulls and 20% are non-nulls. The nulls follow the Hardy Weinberg distribution (ratio) 1:2:1. I have the code below but the p-values are not what I am expecting. I want to use the Cochran Armitage trend test to get the p-values. num.reps=10 num.vars=1000 pi0 = 80 num.subjects = 100 #Create list control list.control and list.treatment #Minor alleles will be from (0.10, 0.30) #num.subjects is the number of subjects in each datamat = matrix(0,num.vars,3) list.treat <- vector("list", 1) # create list for (i in 1: num.reps) { list.treat[[i]]...

Hi, I'm announcing two new releases of opus, along with the first release of the new libopusenc library. First for opus, we just fixed a bad bug in the surround encoding code that would cause very bad quality on signals beyond a certain amplitude. Thanks to Franziska Trojahn and others from HfT Leipzig for finding this issue through their listening test[1] (the quality of the two bad files

Hello list. I'm trying to rebuild the 2.6.9.67.0.20.EL kernel, but it fails even without modifications. How did I try it? Created a (non-root) build environment (not a mock ) Installed the kernel.scr.rpm and did a rpmbuild -ba --target=`uname -m` kernel-2.6.spec 2> prep-err.log | tee prep-out.log The build failed at the end: Processing files: kernel-xenU-devel-2.6.9-67.0.20.EL Checking