search for: exactally

Hi, I have a 3d array as below, I want to make this array to a matrix of p=50(rows) and n=20(columns) with the coverage values . The code before the array is: library(binom) Loading required package: lattice pi.seq<-seq(from = 0.01, to = 0.5, by = 0.01) no.seq<-seq(from = 5, to = 100, by = 5) cp.all = binom.coverage( p = pi.seq, n = no.seq , conf.level = 0.95, method = "exact")

Hi all, I have a dataframe called 'table' in which both factors and numerical values are stored. > dim(table) [1] 990 6 The fist 10 lines of table, to get an idea: > table[1:10,] QueryNo Query type Ret Prec Rec 1 1 Sports exact 1 1 0.01 2 5 Office exact 0 NaN 0.00 3 6 Meeting exact 0 NaN 0.00 4 7 Studio exact 0 NaN 0.00

Hello, I have the following situation: Samba with ldap passdb backend. In my setup I have a group called exact: ------------ dn: cn=exact,ou=Groups,dc=ahm,dc=nl objectClass: posixGroup,sambaGroupMapping cn: exact gidNumber: 1000 sambaSID: S-1-5-21-4269728302-1655870493-3894479995-3001 sambaGroupType: 4 memberUid: gerrit,piet,hornie ------------ maps to the unix group exact: exact

Pardon my ignorance, but is there a difference in cor.test between exact=FALSE and exact=NULL when method=spearman? Take for example: x<-c(1,2,2,3,4,5) y<-c(1,2,2,10,11,12) cor.test(x,y, method="spearman", exact=NULL) This gives an error message, Warning message: Cannot compute exact p-values with ties in: cor.test.default(x, y, method = "spearman", exact = NULL)

Hello, I just thought I would write this in case its useful to anyone. I've used dovecot for a while, as its so easy to set up, its fast and it and just "works". I recently wanted to be able to send via my server after pop3s authentication. I'm also running debian (testing) which utilises exim4 by default. I found no information about how to do it with this combination of

Full_Name: David Simcha Version: 2.10 OS: Windows XP Home Submission from: (NULL) (173.3.208.5) > a <- c(1:10) > b <- c(1:10) > cor.test(a, b, method = "spearman", alternative = "greater", exact = TRUE) Spearman's rank correlation rho data: a and b S = 0, p-value < 2.2e-16 alternative hypothesis: true rho is greater than 0 sample estimates:

Dear List, after updating the exactRanksumTests package I receive a warning that the package is not developed any further and that one should consider the coin package. I don't find the signed rank test in the coin package, only the Wilcoxon Mann Whitney U-Test. I only found a signed rank test in the stats package (wilcox.test) which is able to calculate the exact pvalues but unfortunately

I'm using fisher.exact on a 4x2 table and it seems to work. Does anyone know exactly what is going on? I thought fisher.exact is only for 2x2 tables. Note: I can't use chi-squared because I have a couple of cells with 0 and < 5 observations. -- View this message in context: http://r.789695.n4.nabble.com/fisher-exact-for-2x2-table-tp3481979p3481979.html Sent from the R help

Hi all, One of the things I find most problematic in R is the partial matching of names in lists. Robert and I have discussed this and we believe that having a mechanism that does not do partial matching would be of significant benefit to R programmers. To that end, I have written a patch that modifies the behavior of "[[" as follows: 1. [[ gains an 'exact' argument with

Timothy, I believe you are mistaken. Fisher's exact test give the correct answer even in the face of small expected values for the cell counts. Pearson's Chi-square approximates Fisher's exact test and can give the wrong answer when expected cell counts are low. Chi-square was developed because it is computationally "simple". Fisher's exact test, particularly with tables

Dear All, I have a problem understanding the difference between the outcome of a fisher exact test and a chi-square test (with simulated p.value). For some sample data (see below), fisher reports p=.02337. The normal chi-square test complains about "approximation may be incorrect", because there is a column with cells with very small values. I therefore tried the chi-square with

In an effort to select the most appropriate number of clusters in a mixture analysis I am comparing the expected and actual membership of individuals in various clusters using the Fisher?s exact test. I aim for the model with the lowest possible p-value, but I frequently get p-values below 2.2e-16 and therefore does not get exact p-values with standard Fisher?s exact tests in R. Does anybody know

Does anyone know why wilcox.exact gives W-statistic 6 instead of 12 as indicated below. 12 is the rank sum of group 0 of x, which is the linear statistic computed by wilcox_test. y<-c(1,2,3,4,5) x<-c(1,1,0,0,0) (a) wilcox.exact wilcox.exact(y~x) Exact Wilcoxon rank sum test data: y by x W = 6, p-value = 0.2 alternative hypothesis: true mu is not equal to 0 (b) wilcox_test

Is there a way to search a ferret index and have it only display exact matches? I read in other posts that you should have an untokenized field for the exact matches, but I also use the same field for doing unexact matches too (with the stemming analyzer). Would I need a copy of this field in the index untokenized to do an exact match or is there any sort of flag or something I could pass to

Hi, R-help, I have a group of data from RNA-seq want to be analyzed by Fisher's exact test in R. I want to compare the significant difference of about 30,0000 individuals in two different samples, and I have no idea how to use R, so could you please give me some suggestions or the scripts for Fisher's exact test? Thank you very much. Best, Guanfeng Wang [[alternative HTML version

Dear All, I am trying to calculate the Hardy-Weinberg Equilibrium p-value for 42 SNPs. I am using the function HWE.exact from the package "genetics". In order not to do a lot of coding "by hand", I have a for loop that goes through each column (each column is one SNP) and gives me the p.value for HWE.exact. Unfortunately some SNP have reached fixation and HWE.exact requires a

Dear r-helpers, I have a small dataset (n<50), and I want to compute the Hodges Lehmann exact confidence interval. So far, I know that "pairwiseCI" has the function "HL.diff". The description is as follows : HL.diff calculates the Hodges-Lehmann confidence interval for the difference of locations by calling wilcox.exact in package exactRankTests ; But when I check

Dear R friends, here I write again about the wilcox.exact() problem. I want to compare two sets of categorical data, and in one case it says "negative length vectors not allowed", and in the other one I get the error "cannot allocate vector of length ...". On http://rapidshare.com/files/298621893/wilcox.exact_trouble.Rdata.html you can download the data that cause the

Full_Name: Patrick Hodgson Version: 2.0 OS: solaris 2.9 Submission from: (NULL) (65.94.128.161) The value reported for the parameter W in the function wilcox.exact appears to be incorrect. I have checked the reference in the help file for this function (Myles & Hollander 1973, as well as 2nd ed. 1999 by same authors) and it is clear that W is the sum of the ranks of the data set with the

I'm trying to estimate a cox proportional hazards regression for repeated events (in gap time) with time varying covariates. The dataset consists of just around 6000 observations (lines) (110 events). The (stylized) data look as follows: unit dur0 dur1 eventn event ongoing x 1 0 1 0 0 0 32.23 1 1 2 0 1 1 35.34 1