similar to: KS test and data format

Dear All, I've got a problem with ks.test. I've two realy large vectors, that I'd like to test, but I get an overflow, and the p-value cannot be calculated: > length(genomesv) [1] 390025 > length(scopv) [1] 140002 > ks.test(genomesv, scopv) Two-sample Kolmogorov-Smirnov test data: genomesv and scopv D = 0.2081, p-value = NA alternative hypothesis: two.sided

Hello All, I'd like to create diagrams for dynamic web-pages via a cgi-script that itself uses R. Sadly, I found out that the png and jpeg devices need an X-server :-( , so I cannot use these nice devices. Does any one have any experience using R for on-the-flycreation of graphics for web-pages pages? Any suggestions for workarounds? thanks very much for help, Arne -- Arne Mueller

Hello All, I've created a view stacked barplots where some of the bars should contain a pattern such as stripes. Adjacent bars of the same stack should have the same colour but a different finnling pattern. Is R able to do that? Anyway, it's not the end of the world if not, a workaround would be to export the plot in fig format and then using xfig to make the bar filling striped,

Hello All, I've created a view stacked barplots where some of the bars should contain a pattern such as stripes. Adjacent bars of the same stack should have the same colour but a different finnling pattern. Is R able to do that? Anyway, it's not the end of the world if not, a workaround would be to export the plot in fig format and then using xfig to make the bar filling striped,

Hello, I'm trying to put a mathematical expression into a legend, but R complains about a syntax error. Basically i'd like to do this: legend.text = c(expression(x < 10), expression(x >= 10)) The manual says that one can only pass mathematical expressions to axis, text etc. but not to the legend command? Is there a workaround for this? thanks a lot for help, Arne -- Arne

Hello, I've just started R, and I'm getting a bit mad using it. I've managed to produce a barplot with the labels for the ytick marks placed horizontally (perpendicular to the y-axis) usiing par(las=1). The problem is that most of my labels are in part beyond the plotting area because they are rather long (e.g. "H. sapiens", "D. melanogaster" ...). What is the

Hello, I've read in a data file as a frame and now I'd like the columns to be rows and the rows to be columns. What's the easiest way to do this in R? > class(d) [1] "data.frame" > rownames(d) [1] "98x101" "40x98" "30x40" "0x30" > colnames(d) [1] "H..sapiens" "C..elegans"

Dear All, I'm getting confused with the concept R uses to do regression using lm. I'm afmiliar with gnuplot and the build-in fit command, but couldn't get R's lm to work on my data. I know that my data follows a powerlaw or maybe an exponential function, and I'd like to determine the best fitting factors for the formula: a*x^b where b < 0. I've tried thge follwoing:

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)

Hello, While doing test of normality under R and SAS, in order to prove the efficiency of R to my company, I notice that Anderson Darling, Cramer Van Mises and Shapiro-Wilk tests results are quite the same under the two environnements, but the Kolmogorov-smirnov p-value really is different. Here is what I do: > ks.test(w,pnorm,mean(w),sd(w)) One-sample Kolmogorov-Smirnov test data: w D

> x <- runif(100) > y <- runif(100) > ks.test(x,y) Two-sample Kolmogorov-Smirnov test data: x and y D = 0.11, p-value = 0.5806 alternative hypothesis: two-sided ok I expected that, but: > ks.test(runif(100), "runif") One-sample Kolmogorov-Smirnov test data: runif(100) D = 0.9106, p-value < 2.2e-16 alternative hypothesis: two-sided How

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

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 .... >

Dear All. I have the following table that I want to analyze using multinom function freq segments sample 4271 Seg1 tumour 4311 Seg2 tumour 3515 Seg1 normal 3561 Seg2 normal I want to compare model with both factors to the one where only sample is present. model1=multinom(freq~segments+sample,data=table) model2=multinom(freq~ sample,data=table)

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: 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

In message <Pine.GSO.4.31.0107010731110.7616-100000@auk.stats>, Prof Brian D Ripley <ripley@stats.ox.ac.uk> writes > >You do realize that the Kolmogorov tests (and the Kolmogorov-Smirnov >extension) assume continuous distributions, so the distribution theory >is not valid in this case? > >S-PLUS does stop you doing this: > >> ks.gof(o,

The note to 1004 says "fixed for 1.3.1" Uh. No. It ain't. The problem was more serious than guessed as even the simplest testing would show. For example, Example 5.4 in Hollander and Wolfe (Nonparametric Statistical, Methods, 2nd ed., Wiley, 1999, pp. 180-181) R Version 1.3.1 (SuSE Linux 7.1) > X <-

I am not sure whether I'm doing something wrong or there is a bug in the documentation of ks.test. Following the posting guide, as I'm not sure, I haven't found this in the bug tracker, and the R FAQ says that stats is an Add-on package of R, I think this is the place to send it. ?ks.test provides the example <QUOTE> # Does x come from a shifted gamma distribution with shape 3

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