similar to: output Shapiro-Wild results to a table

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

In the course of applying Shapiro-Wilk to 100,000 samples of 60 items from 100,000 different distributions, I encountered a fatal error in apply(). This can be reconstructed as follows, using the attached data file distr.dat containing 2 lines of my original 100,000-line file: > version _ platform Windows arch x86 os Win32 system x86, Win32 status

Full_Name: Jason Polak Version: R version 2.5.0 (2007-04-23) OS: Xubuntu 7.04 Submission from: (NULL) (137.122.144.35) Dear R group, I have noticed a strange anomaly with the shapiro.test() function. Unfortunately I do not know how to calculate the shapiro test P values manually so I don't know if this is an actual bug. So, to produce the results, run the following code: pvalues = 0; for

R Users: My question is probably more about elementary statistics than the mechanics of using R, but I've been dabbling in R (version 2.2.0) and used it recently to test some data . I have a relatively small set of observations (n = 12) of arsenic concentrations in background groundwater and wanted to test my assumption of normality. I used the Shapiro-Wilk test (by calling shapiro.test()

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

Hi, I am reading in a dataframe from a CSV file. It has 70 columns. I do not have any kind of unique "row id". rawdata <- read.table("r_work/train_data.csv", header=T, sep=",", na.strings=0) When training an svm, I keep getting an error So, as an experiment, I wrote the data back out to a new file so that I could see what the svm function sees.

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 not so sure about an error note I got when using shapiro.test. I imported some data into R by wrinting it into a .txt file via > tab1<-read.table("etc....txt",header=T) > attach(tab1) The following object(s) are masked _by_ .GlobalEnv : ozon > ozon$V1 [1] 2.5 3.0 5.6 4.7 6.5 6.7 1.7 5.3 4.6 7.4 5.4 4.1 5.1 5.6 5.4 6.1 7.6[18] 6.2 6.0 5.5 5.8 8.2 3.1 5.8 2.6 Now

I have three files of data which are available at http://zhangw.com/ R/, varied at the number of data. I tried to use R to analyze using shapiro.test, ks.test, and t.test. t.test ran as expected, however, when I run shapiro.test and ks.test commands, error message always occurred. Error message for shapiro.test is "Error in "[.data.frame"(x, complete.cases(x)) : undefined

Hi, In ?shapiro.test, there seems to be no option to pass mean and sd information of the Normal distribution which I want to compare my sample data to. For example in the code below, I want to test my sample to N(0, 10). shapiro.test(rnorm(100, mean = 5, sd = 3)) Is there any way to pass the information of the benchmark normal distribution?

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

Hi all! I tried to perform Shapiro-Wilk test for my sample of 243 values. > Us [1] -10.4 -13.1 -12.2 38.1 -18.8 -13.3 -11.7 29.3 49.7 6.8 12.7 16.3 [13] 5.8 -0.7 -29.4 4.1 38.8 -1.4 8.8 15.6 32.9 -5.3 19.1 35.8 [25] 4.0 -1.5 0.6 -4.2 -10.0 -4.0 1.1 48.9 -21.0 -5.3 5.8 -10.8 [37] 21.9 8.2 -3.2 -3.9 -2.3 12.6 -4.7 -8.0 11.8 27.4 -9.5 -20.8 [49]

Dear all, I am trying to create beanplots from a dataset for which boxplot works fine. (MACOS, R 2.8.1 GUI 1.27 Tiger build 32-bit (5301)) I am getting the following error message: Error in shapiro.test(x) : sample size must be between 3 and 5000 I am not even sure why the shapiro.test is being used, but is there any workaround ? Thanks ! Markus [[alternative HTML version deleted]]

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,

Hello, I have tested a distribution for normality using the Shapiro-Welch statistic. The result of this is the following: Shapiro-Wilk normality test data: mydata W = 0.9989, p-value = 0.8791 I know that the p-value > 0.05 (for my purposes) means that the data IS normally distributed but what I am not sure is with the W value, what values tell me that the data is normally

Hi everybody, somehow i dont get the shapiro wilk test for normality. i just can?t find what the H0 is . i tried : shapiro.test(rnorm(5000)) Shapiro-Wilk normality test data: rnorm(5000) W = 0.9997, p-value = 0.6205 If normality is the H0, the test says it?s probably not normal, doesn ?t it ? 5000 is the biggest n allowed by the test... are there any other test ? ( i know qqnorm

Hi, I have a dataframe (try.1) with  date/time and temperature columns, and the date/time is in POSIXct fomat. Sample included below. I would like to to try decompose () or stl() to look at the trends and seasonality in my data, eventually so that  I can  look at autocorrelation.  The series is 3 years of water temperature with clearly visible seasonal periods. Right now, if I try decompose,

1) The .RData file (and S .Data area) are cputype dependent. When R is used from different types of machines (say, HP and Sun) that share a common filesystem (say afs or dfs) then loading the wrong type of .RData file can lead to mysterious behaviour. In my environment, undergraduate students are the most likely to log into different cputypes, and they end up being quite confused. To

Hi The shapiro.test function outputs a value of the W statistic, which should be 1 if the distribution is normal, and a p-value for the test (as the documentation states). I'm a bit confused with some results. I'm getting a W=0.9977 and a p-value=0.1889. I was expecting that a W of 0.9977 would tell me that the distribution is normal so p-value should be small ... What am I missing ?

hey all, I'm just getting used to R and i'm having issues when it comes to reading my data in rows rather than columns. any good advice would be much appreciated ! here is the error: > data1 <- read.table(file.choose(),header=T) > x1 <- c(data1[1,1:5]) > shapiro.test(x1) Error in sort.int(x, na.last = na.last, decreasing = decreasing, ...) : 'x' must be atomic