similar to: multivariate Shapiro Wilks test

Dear List, Is there any function in R to generate multivariate F distribution with given correlation/covariance matrix? Actually, I just want to generate some 2-dimentional non-normal data sets (skewed) for low (may be around 0.3 cor coeff.) negatively and also positively correlated variables ? Thanks in advance. Anna

Dear List, I would like to ask about package RGtk2 with which I have a problem. I will very much appreciate if somebody could tell me what I need to do. I need to install a package scdMicro and it depends on gWidgetsRGtk2. I am working on MAC, version 10.5.8. When I try to load gWidgetsRGtk2 (or RGtk2), it asks me: "Instal GTK+?" I installed Gtk+ from CRAN, and added a path: export

Hello all, I tried several experiments with the mshapiro.test package in R and compared it with the energy package to test for multivariate normality and find that the mshapiro.test is not consistent which is a bit concerning and has suspicious behavior. On the other hand the energy test seems to be a more appropriate test for testing multivariate normality in any dimension. I looked for the

Hi all, I am newbie in using R software and also doing statistical test. I want to know if my data in in normal distribution. I have 2 groups of data and I did calculate Shapiro Wilks using R software. Here is the results: Group 1: W = 0.9206, p-value = 0.01683 Group 2: W = 0.9626, p-value = 0.4694 I am not quite sure what default confidence level (CF) is used in calculating Shapiro Wilks.

Dear all, I want to save the p-value from mshapiro.test(mvnormtest). But mshapiro.test(mvnormtest) gives a list with class "htest" containing statistic, p.value, method and data.name as a whole. How do I save only p-value from the result? Thanks a lot!

Good Night I made different test to check normality and multinormality in my dataset, but I don´t know which test is better. To verify univariate normality I checked: shapiro.test, cvm.test, ad.test, lillie.test, sf.test or jaque.bera.test and To verify multivariate normal distribution I use mardia, mvShapiro.Test, mvsf, mshapiro.test, mvnorm.e. I have a dataset with almost 1000 data and 9

My stat textbook tells me that using Shapiro-Wilk test for each variable one by one is not equal to a test for multivariate normality as a whole. Does R have a function of testing for multivariate normality? Thanks. Hongsheng (Hank) Liao, Ph.D. Lab Manager Center for Quantitative Fisheries Ecology 800 West 46th Street Old Dominion University Norfolk, Virginia 23508 Phone:757.683.4571

Hello, Could someone help me to explain the VERY big difference in applying two tests on multivariate normality: library(mvnormtest) data(EuStockMarkets) mshapiro.test(t(EuStockMarkets[15:29,1:4])) Shapiro-Wilk normality test data: Z W = 0.8161, p-value = 0.005955 and library(energy) mvnorm.etest( EuStockMarkets[15:29,1:4] ) Energy test of multivariate normality:

Dear all, I have a multivariate dataset containing 100,000 or more points. I want find the p-value for the dataset of points coming from a particular multivariate normal distribution With mean vector u Covariance matrix s2 So H0: points ~ MVN( u, s2) H1: points not ~ MVN( u, s2) How do I find the p-value in R? To me this is a likelihood ratio test problem. In H0 the parameters are

Hi, I have a question about the p-value of mshapiro test. I simulated data from bivariate normal 1000 times and used mshapiro test to see how many times the test would reject the null hypothesis when the p-value is 0.05. The answer should be around 50 since the p-value is 0.05. But I got a much higher value. Here is the R code I used and the result.

Dear all, I got this error message > library(dprep) > mardia(Savg) Error in cov(data) : 'x' is empty But with the same data, I got > library(mvnormtest) > mshapiro.test(Savg) Shapiro-Wilk normality test data: Z W = 0.9411, p-value = 0.6739 What does the error message "Error in cov(data) : 'x' is empty" mean? Thanks a lot! Jiao

Can anybody tell me the exact meaning of the $statistic and $p.value calculated by shapiro.test? Unfortunately it is not covered in my few text books, and I cannot find the explanation in the R documentatiom or on-line. If I have a test statistic, T, which is Normally distributed with mean=m and sd=s under the null hypothesis, then I can convert T to a p-value (one-sided) using: p <- pnorm(T,

I'm pretty new to R and are trying to do some reliable normality testing... but, can't find the Shapiro Wilk test in R Does some experienced user have such a function that will be wanting to share with me? Or there is maybe some other way to get hte Shapiro Wilk test done... I'll appreciate any hint on this, Thanks -- *********************** Horacio Samaniego Dep. Ecologia P.

What is the formula used in Shapiro-Wilk Statistic? Thanks Eduardo (S?o Paulo/ Brazil)

Hi everybody, Does anyone know what problem may be with this test. I am applying 5 different normality tests and use p-values for them, but for some reason S-W gives me NA, while sample size is 100. Any ideas? Thanks a lot! [[alternative HTML version deleted]]

Greetings! I want to have the coefficients that R uses in shapiro.test() for the Shapiro-Wilk test for a prticular sample size, i.e. the a[i] in W = Sum(a[i]*x[i])/(Sum(x[i] - mean(x))^2) (where the x[i] are sorted). Two questions: Q1: Is there a readymade R function from which I can extract these? Q2: I was wondering if I might be able to modify the code for the function shapiro.test() so

Hi, does the shapiro wilk test in R-1.3.0 work correctly? Maybe it does, but can anybody tell me why the following sample doesn't give "W = 1" and "p-value = 1": R> x<-1:9/10;x [1] 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 R> shapiro.test(qnorm(x)) Shapiro-Wilk normality test data: qnorm(x) W = 0.9925, p-value = 0.9986 I can't imagine a sample being

Hi, I am trying to create a table with information from Shapiro Wilk's test of normality. However, it fails due to lack of sample size, it says, but the way I see it, this is not a problem. (See the table of sample sizes (almost) at the bottom). Applying a different function using a similar ftable call is not a problem (See the bottom table). This is R 2.1.0 on Linux (Gentoo). /Fredrik

>>> Ted Harding <Ted.Harding at manchester.ac.uk> 14/07/2008 00:16 >>> >said: >What constitutes "reasonable doubt" can become a very interesting >question, but there are some crimes for which it has a definite >statistical interpretation Warning for potential courtgoers: "reasonable doubt" NEVER has a direct statistical interpretation in a

Hello, I was wandering if it is possible to perform on a dataframe called 'all' a shapiro wilk normality test for COUNTS by variable Group ACTIVITY? Could it be done using plyer? I saw an eg that applies to an array but not to a dataframe: lapply(split(dataset1$Height,dataset1$Group),shapiro.test) Any thoughts would be much appreciated. My dataframe is in shape: dat ACTIVIT