similar to: Questions about ks.test function {stats}

Hello, Today I was investigating ks.test() with two numerical arguments (x and y) and was left a bit confused about the policy behind handling ties. I might be missing something, so sorry in advance, but here is what confuses me: The documentation states: "The presence of ties always generates a warning, since continuous distributions do not generate them" But when I run a test with

HI, I've noticed what I think is an incorrect behavior of stats::psmirnov function and consequently of ks.test when run in an exact mode. For example: psmirnov(1, sizes=c(50, 50), z=1:100, two.sided = FALSE, lower.tail = F, exact=TRUE) produces 2.775558e-15 However, the exact value should be 1/combination(100, 50), which is 9.9e-30. While the absolute error is small, the relative error is

Dear R experts, Greetings from China! I'm Zhang in the College of Education, Zhejiang University, and I am recently running a meta-analysis. Since research using the randomized controlled trial (RCT) often dismissed reporting the correlation (r) between multivariate outcomes, for instance, a study measuring students' gains on problem solving skills with three aspects and reported the

Full_Name: Thomas Waterhouse Version: 2.9.1 OS: OS X 10.5.7 Submission from: (NULL) (216.239.45.4) ks.test uses a biased approximation to the p-value in the case of the two-sample test with ties in the pooled data. This has been justified in R in the past by the argument that the KS test assumes a continuous distribution. But the two-sample test can be extended to arbitrary distributions by a

Hi there! I have two little different data. One is a computer test on people, the other is a paper and pencil test. two boxplots show me that the data is almost the same. So now I'd like to know if I could handle all data as one, by testing with ks.test: ==== > ks.test(el$angststoer, fl$angststoer) Two-sample Kolmogorov-Smirnov test data: el$angststoer and fl$angststoer D =

Full_Name: Andrew Grant McDowell Version: R 1.1.1 (but source in 1.3.0 looks fishy as well) OS: Windows 2K Professional (Consumer) Submission from: (NULL) (194.222.243.209) In article <xeQ_6.1949$xd.353840@typhoon.snet.net>, johnt@tman.dnsalias.com writes >Can someone help? In R, I am generating a vector of 1000 samples from >Bin (1000, 0.25). I then do a Kolmogorov Smirnov test

I frequently want to test for differences between animal size frequency distributions. The obvious test (I think) to use is the Kolmogorov-Smirnov two sample test (provided in R as the function ks.test in package ctest). The KS test is for continuous variables and this obviously includes length, weight etc. However, limitations in measuring (e.g length to the nearest cm/mm, weight to the nearest

Full_Name: t. avery Version: 2.0.0 OS: windows xp / Linux Submission from: (NULL) (131.162.134.159) ks.test does not produce the correct output. If given the script: d1 <- c(53.63984674,0.383141762,1.915708812,0.383141762,10.72796935,6.896551724,20.30651341,5.747126437,0) d1 d2 <- c(76.43312102,15.2866242,3.821656051,1.27388535,0,0.636942675,1.27388535,0.636942675,0.636942675) d2

All, Happy World Cup and Wimbledon. This morning finds me with the first of my many daily questions. I am running a ks.test on residuals obtained from a regression model. I use this code: > ks.test(Year5.lm$residuals,pnorm) and obtain this output One-sample Kolmogorov-Smirnov test data: Year5.lm$residuals D = 0.7196, p-value < 2.2e-16 alternative hypothesis: two.sided Warning

[In future, please press reply all as there might be others in the mailing list who can help you] Without a (short) reproducible example, it would be difficult to say. BTW, I think you have mistyped the error/warning message. Does it actually say "cannot compute _correct_ p-value" or "cannot compute _exact_ p-value". See example below. > wilcox.test( 1:3, 1:10 )

Dear R users I am using KS test to compare two different distribution for the same variable (temperature) for two different time periods. H0: the two distributions are equal H1: the two distributions are different ks.test (temp12, temp22) Two-sample Kolmogorov-Smirnov test data: temp12 and temp22 D = 0.2047, p-value < 2.2e-16 alternative hypothesis: two-sided Warning message: In

Hello! I have two matrices of equal dimension ll and lu that I want to do a ks.test on corresponding rows in these matrices (dim(ll) is [1] 101 100). If I do e.g. > ks.test(ll[50,],lu[50,]) just for testing, it displays a lot of numbers, and some more info: [116] -3.000000e-02 -4.000000e-02 -4.000000e-02 -3.000000e-02 -4.000000e-02 [121] -3.000000e-02 -4.000000e-02 -3.000000e-02 -2.000000e-02

Hi, I am trying the following: library(ismev) library(evd) fit <- gev.fit(x,show=FALSE) ks.test(x,pgev,fit$mle[1],fit$mle[2],fit$mle[3]) but I am getting: Warning message: cannot compute correct p-values with ties in: ks.test(x, pgev, fit$mle[1], fit$mle[2], fit$mle[3]) where x is: [1] 239 38 1 43 22 1 5 9 15 6 1 9 156 25 3 100 6 [18] 5 100

Dear All, I wonder if there is now an implementation of a modified KS test that can handle ties? Steve. [[alternative HTML version deleted]]

I have to start by saying that I am new to R, so I might miss something crucial here. It seems to me that the results of friedman.test and ks.test are "wrong". Now, obviously, the first thing which crossed my mind was "it can't be, this is a package used by so many, someone should have observed", but I can't figure out what it might be. Problem: let's start with

I'm using ks.test() to compare two different measurement methods. I don't really know how to interpret the output in the absence of critical value table of the D statistic. I guess I could use the p-value when available. But I also get the message "cannot compute correct p-values with ties ..." does it mean I can't use ks.test() for these data or I can still use the D

1) When running ks.test, I am getting the following error after the test presents its result:: 'ks.test(x, y) : cannot compute correct p-values with ties' I wonder what means and what causes it. 2) Also, how do I calculate an effect size from this statistic? R.

Hi, Everyone! I've installed samba + print$ driver + cups successfully on my Debian Box, and I've made a simple page count program for the printed PCL and postscript files, it runs nicesly, but one problem I encountered is that I can't check the "Advanced " option on for the samba printer (I've tried to check them, but it does not take effect), while I can do it well

On Sun, 1 Jul 2001 mcdowella@mcdowella.demon.co.uk wrote: > Full_Name: Andrew Grant McDowell > Version: R 1.1.1 (but source in 1.3.0 looks fishy as well) > OS: Windows 2K Professional (Consumer) > Submission from: (NULL) (194.222.243.209) Please upgrade: we've found a number of Win2k bugs and worked around them since then, let alone teh bug fixes and improvements in R .... >

Hi everybody, while performing ks.test for a standard exponential distribution on samples of dimension 2500, generated everytime as new, i had this strange behaviour: >data<-rexp(2500,0.4) >ks.test(data,"pexp",0.4) One-sample Kolmogorov-Smirnov test data: data D = 0.0147, p-value = 0.6549 alternative hypothesis: two.sided >data<-rexp(2500,0.4)