similar to: how to interpret KS test

R-help - I have this set of aggregated tables (sample data below via dput()). And I would like to have delayValue as the column variables with the "temp" (temp1, temp2, temp3) values as the row variables. However I would like to have the temp variables *aggregated into single rows* so that I have the frequency ("Freq" | counts) of each time each "delayValue" occurs

Let me explain the subject title, store provider is Hackey, he''s a NPC that sells items to my users. <h1>Welcome to Hackey''s!</h1> <h3>Catalog</h3> <table border="2" bordercolor="red"> <% for items in @items -%> <% temp12 = Item.find(items.item_id) -%> <tr><td><%= @temp12.name

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)

> 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

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

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 Im new in R I have a necdf data set that I want to plot : this is my data set [1] "file Tmax.DJF.daily.1981_1999.echama2.nc has 4 dimensions:" [1] "longitude Size: 127" [1] "latitude Size: 110" [1] "ht Size: 1" [1] "t Size: 1680" [1] "------------------------" [1] "file Tmax.DJF.daily.1981_1999.echama2.nc has 1

Hi, I have a problem with Kolmogorov-Smirnov test fit. I try fit distribution to my data. Actualy I create two test: - # First Kolmogorov-Smirnov Tests fit - # Second Kolmogorov-Smirnov Tests fit see below. This two test return difrent result and i don't know which is properly. Which result is properly? The first test return lower D = 0.0234 and lower p-value = 0.00304. The lower 'D'

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 =

Hi! how can I do the Kolmogorov Smirnov test for discrepancy between the estimated and empirical tails? Regards Anuradha [[alternative HTML version deleted]]

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

Dear all, One can use ks.test(x,y) for a one-sample kolmogorov-smirnov test: x being the data sample y being a string specifying a distribution I notice the help on ks.test does not tell you how to get such a list. Is this a hole in my R knowledge? Where can I get a list of the strings specifying the possible distributions? and more specifically What would be the string and following

Hello, I want to do normality test on my data I write this but I don't understand the display of the results ks.test(data,"pnorm") In fact I want to know if my data is a normal distribution. I have to check the p-value or D? Thanks. _____________________________________________________________________________ l [[alternative HTML version deleted]]

Hi, Interpretation problem ! so what i did is by using the: >fit1 <- fitdist(vectNorm,"beta") Warning messages: 1: In dbeta(x, shape1, shape2, log) : NaNs produced 2: In dbeta(x, shape1, shape2, log) : NaNs produced 3: In dbeta(x, shape1, shape2, log) : NaNs produced 4: In dbeta(x, shape1, shape2, log) : NaNs produced 5: In dbeta(x, shape1, shape2, log) : NaNs produced 6: In

Hi everyone I am new to R and have a question about missing values. I am trying to do a cluster analysis of monthly temperatures and my data are 14 columns with spatial coordinates (lat,lon) and 12 monthly values: /lat - lon - temp1 - //temp2 - temp3 - .... - //temp12/ If I omit missing values (my missing values are 99.00) with /mydata <- na.omit(mydata)/ every row with a

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

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 <-

hello everybody, here I have a question regarding printing of the constants( like 2 .63 etc.,) present in the instruction while iterating over the instructions within a basic block . I am able to print the vaiables but not the constants. Can you please tell me how to get the constants printed out while iterating over the instructions because the constants do not have names as the variables do(

for a silly question, wondering how to test fit with the one sample as follow. I have read _fitting distributions with R_, but that doesn't answer my specific question. inclined to use Kolmogorov-Smirnov D, and its associative p value. much appreciation! X20.001 232 93 84 185 336 417 228 199 2110 1411 612 1913 1314 3015

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