[R] Re: R: log-normal distribution and shapiro test
Siegfried Gonzi
siegfried.gonzi at stud.uni-graz.at
Wed Nov 17 15:01:37 CET 2004
Hi:
Thanks for your answer.
Do you know how to test whether the data would fit to a gamma-distribution?
How can I call fBasics?
Note: I installed R-language on my Macintosh today; I have used the
binary -- pre compiled -- package.
Some of the R-help facilties do not function on my Mac.
Again to my data: How can I compute the skew? I think I lack some basic
packages - right?
The curious things actually is that the median and the mean are quite
similar, e.g. 0.19 and 0.2 respectively; the skew is about 1.0 (I
calculated the skew by my own computer code in Bigloo).
The problem actually is: my boss expects from me that I make some tests;
personally I am a bit generous and everything is a Gaussian or
log-Gaussian distribution, because how can I be sure that the underlying
data to not have any serious flaws? Statistics is black art - right?
Regards,
S. Gonzi
Vito Ricci wrote:
>Hi,
>
>from what you're writing:
>"The logaritmic transformation
>"shapiro.test(log10(y))" says: W=0.9773, p-value=
>2.512e-05." it seems the log-values are not
>distributed normally and so original data are not
>distributed like a log-normal: the p-value is
>extremally small!
>
>Other tests for normality are available in package:
>nortest
>
>compare the log-transformation of your ecdf with
>normal cdf: see ? ecdf
>
>use qqnorm and qqplot
>
>did you calculate skewness and kurtosis? see in
>package fBasics.
>
>I remember to you that the log-normal distribution as
>three parameters: shape parameter, location parameter
>and scale parameter. Transfroming by the simple log,
>you are missing the location parameter, or implicitely
> you assuming is =0.
>
>See:
>http://www.itl.nist.gov/div898/handbook/eda/section3/eda3669.htm
>for more news about log-normal distribution.
>
>I hope I give you a little help.
>Best
>Vito
>
>
>
>
>you wrote:
>
>Hello:
>
>Yes I know that sort of questions comes up quite
>often. But with all due
>respect I din't find how to perform what I want. I am
>searching archives
>and bowsing manuals but it isn't there, though, it is
>a ridiculous
>simple task for the experienced R user.
>
>I have data and can do the following with them:
>
>==
>hist(y, prob=TRUE)
>lines(density(y,bw=0.03)
>==
>
>The result actually is a nice histogram superimposed
>by a line plot.
>
>The histogram is a bit skewed to the left. My
>assumption actually is
>that a log-normal transformation would cure the
>problem. But how the
>hell can one plot such a density function or Gaussian
>function which has
>logarithmic scales on x axis.
>
>For example I tried:
>
>==
>plot(hist(y),log="x")
>
>or
>
>plot(hist(log10(y)),log="x")
>==
>
>But with no avail. I want my axis like: 1,10,100
>
>
>
>What would be other methods to test whether the data
>are logaritmically
>distributed.
>
>A last question to the Shapiro-Wilk test. Were can I
>get critical
>parameters? I mean I get for my distribution:
>W=0.9686, p-value=6.887e-07.
>What does that mean? Yes I have got some books about
>statics, but none
>of them says what one should do with the values then.
>The logaritmic
>transformation "shapiro.test(log10(y))" says:
>W=0.9773, p-value= 2.512e-05.
>
>Sorry for disturbing you. Although, it is really no
>homework. I need it
>for my Phd in physics; after a lengthy computation on
>the computer I
>would like to go to see whether the outputs are
>log-normal or normal
>distributed.
>
>Regards,
>Siegfried Gonzi
>==
>University of Graz
>Institute for Physics
>Tel.: ++43-316-380-8620
>
>=====
>Diventare costruttori di soluzioni
>Became solutions' constructors
>
>"The business of the statistician is to catalyze
>the scientific learning process."
>George E. P. Box
>
>
>Visitate il portale http://www.modugno.it/
>e in particolare la sezione su Palese http://www.modugno.it/archivio/cat_palese.shtml
>
>
>
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