Displaying 20 results from an estimated 2000 matches similar to: "ks.test"
2011 Oct 06
2
KS test and theoretical distribution
> 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
2005 Mar 18
1
Pb with ks.test pvalue
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
2006 Feb 03
2
Problems with ks.test
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)
2006 Dec 15
2
ks.test "greater" and "less"
Hello r-group
I have a question to the ks.test.
I would expect different values for less and greater between data1 and
data2.
Does anybody could explain my point of misunderstanding the function?
data1<-c(8,12,43,70)
data2<- c(70,43,12,8)
ks.test(data1,"pnorm")
ks.test(data1,"pnorm",alternative ="less") #expected < 0.001
2006 Jul 09
1
KS Test Warning Message
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
2001 Jul 01
1
(PR#1007) ks.test doesn't compute correct empirical
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 ....
>
2010 Aug 20
3
how to interpret KS test
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
2001 Jul 02
2
Shapiro-Wilk test
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
2008 Mar 08
1
ks.test troubles
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 =
2009 Sep 08
1
Unexpected behavior in friedman.test and ks.test
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
2002 Mar 26
3
ks.test - continuous vs discrete
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
2010 Nov 11
2
Kolmogorov Smirnov Test
I'm using ks.test (mydata, dnorm) on my data. I know some of my
different variable samples (mydata1, mydata2, etc) must be normally
distributed but the p value is always < 2.0^-16 (the 2.0 can change
but not the exponent).
I want to test mydata against a normal distribution. What could I be
doing wrong?
I tried instead using rnorm to create a normal distribution: y = rnorm
2006 May 09
4
ks.test one-sample - where can I get a list of the strings specifying the distribution?
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
2011 Oct 13
1
KS test
Hi!
how can I do the Kolmogorov Smirnov test for discrepancy between the
estimated and empirical tails?
Regards
Anuradha
[[alternative HTML version deleted]]
2005 Jun 27
1
ks.test() output interpretation
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
2007 Feb 23
4
using "integrate" in a function definition
Dear list members,
I'm quite new to R, and though I tried to find the answer to my probably
very basic question through the available resources (website, mailing
list archives, docs, google), I've not found it.
If I try to use the "integrate" function from within my own functions,
my functions seem to misbehave in some contexts. The following example
is a bit silly, but
2010 Aug 04
4
KS Test question (2)
Hi R Users,
I have two vectors, x and y, of equal length representing two types of
data from two studies. I would like to test if they are similar enough
to use them interchangeably. No assumptions about distributions can be
made (initial tests clearly show that they are not normal).
Here some result:
Two-sample Kolmogorov-Smirnov test
data: x and y
D = 0.1091, p-value < 2.2e-16
alternative
2011 Jun 10
3
Test if data uniformly distributed (newbie)
Hello,
I have a bunch of files containing 300 data points each with values from 0
to 1 which also sum to 1 (I don't think the last element is relevant
though). In addition, each data point is annotated as an "a" or a "b".
I would like to know in which files (if any) the data is uniformly
distributed.
I used Google and found out that a Kolmogorov-Smirnov or a Chi-square
2001 Oct 26
1
ks.test (PR#1004)
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 <-
2011 Apr 27
3
Kolmogorov-Smirnov test
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'