Displaying 20 results from an estimated 5000 matches similar to: "Goodness fit test HELP!"
2009 Jan 26
1
Goodness of fit for gamma distributions
I'm looking for goodness of fit tests for gamma distributions with large data
sizes. I have a matrix with around 10,000 data values in it and i have
fitted a gamma distribution over a histogram of the data.
The problem is testing how well that distribution fits. Chi-squared seems to
be used more for discrete distributions and kolmogorov-smirnov seems that
large sample sizes make it had to
2005 Jan 11
3
Kolmogorov-Smirnof test for lognormal distribution with estimated parameters
Hello all,
Would somebody be kind enough to show me how to do a KS test in R for a
lognormal distribution with ESTIMATED parameters. The R function
ks.test()says "the parameters specified must be prespecified and not
estimated from the data" Is there a way to correct this when one uses
estimated data?
Regards,
Kwabena.
--------------------------------------------
Kwabena Adusei-Poku
2004 Nov 17
1
R: log-normal distribution and shapiro test
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
2005 Jan 13
2
chisq.test() as a goodness of fit test
Dear R-Users,
How can I use chisq.test() as a goodness of fit test?
Reading man-page I?ve some doubts that kind of test is
available with this statement. Am I wrong?
X2=sum((O-E)^2)/E)
O=empirical frequencies
E=expected freq. calculated with the model (such as
normal distribution)
See:
http://www.itl.nist.gov/div898/handbook/eda/section3/eda35f.htm
for X2 used as a goodness of fit test.
Any
2004 Sep 20
3
montecarlo simulation
Hy!
I would like to know how run a montecarlo simulation with R.
Thank you!!!!
Francesca Matalucci
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2005 Jan 25
1
Fitting distribution with R: a contribute
Dear R-useRs,
I've written a contribute (in Italian language)
concering fitting distribution with R. I believe it
could be usefull for someones. It's available on CRAN
web-site:
http://cran.r-project.org/doc/contrib/Ricci-distribuzioni.pdf
Here's the abstract:
This paper deals with distribution fitting using R
environment for statistical computing. It treats
briefly some
2004 Jul 21
2
Testing autocorrelation & heteroskedasticity of residuals in ts
Hi,
I'm dealing with time series. I usually use stl() to
estimate trend, stagionality and residuals. I test for
normality of residuals using shapiro.test(), but I
can't test for autocorrelation and heteroskedasticity.
Is there a way to perform Durbin-Watson test and
Breusch-Pagan test (or other simalar tests) for time
series?
I find dwtest() and bptest() in the package lmtest,
but it
2008 May 04
2
Ancova_non-normality of errors
Hello Helpers,
I have some problems with fitting the model for my data...
-->my Literatur says (crawley testbook)=
Non-normality of errors-->I get a banana shape Q-Q plot with opening
of banana downwards
Structure of data:
origin wt pes gender
1 wild 5.35 147.0 male
2 wild 5.90 148.0 male
3 wild 6.00 156.0 male
4 wild 7.50 157.0 male
5 wild 5.90
2005 Jan 17
3
Skewness test
Hi,
is there a test for the H0 skewness=0 (or with skewness as test
statistic and normality as H0) implemented in R?
Thank you,
Christian
***********************************************************************
Christian Hennig
Fachbereich Mathematik-SPST/ZMS, Universitaet Hamburg
hennig at math.uni-hamburg.de, http://www.math.uni-hamburg.de/home/hennig/
2010 Jun 16
2
Fitting Gamma distribution
I'm looking for goodness of fit tests for gamma distributions with large data
sizes and for different data.
I have a matrix with around 4.000 data values in it and i have fitted a
gamma distribution with "fitdistr".
You can see the example:
> fitdistr(corpo,"gamma",lower=0.001)
Errore in optim(x = c(5000, 5000, 5000, 5000, 5000, 5000, 5000, 5000,
5000, :
2005 Jan 13
2
multivariate diagnostics
Hi, there.
I have two questions about the diagnostics in multivarite statistics.
1. Is there any diagnostics tool to check if a multivariate sample is from
multivariate normal distribution? If there is one, is there any function
doing it in R?
2. Is there any function of testing if two multivariate distribution are
same, i.e. the multivariate extension of Kolomogrov-Smirnov test?
Thanks for
2007 May 18
1
Goodness-of-fit test for gamma distribution?
Hi all,
I am wondering if anyone has written (or knows of) a function that
will conduct a goodness-of-fit test for a gamma distribution. I am
especially interested in test statistics have some asymptotic
parametric distribution that is independent of sample size or values
of fitted parameters (e.g., a chi-squared distribution with some
fixed df), because I want to fit gamma distributions to
2005 Feb 22
2
estimate the parameter of exponential distribution, etc.
Given a numeric vector of observations, does R have any generic way to estimate the parameters of commonly used distributions (exponential, gamma, etc.) without numerically optimizing the likelihood function?
Thanks,
David
_______________________________________
David R. Bickel http://davidbickel.com
Research Scientist
Pioneer Hi-Bred International
Bioinformatics & Exploratory Research
7250
2010 Jun 24
4
Simple qqplot question
I am a beginner in R, so please don't step on me if this is too
simple. I have two data sets datax and datay for which I created a
qqplot
qqplot(datax,datay)
but now I want a line that indicates the perfect match so that I can
see how much the plot diverts from the ideal. This ideal however is
not normal, so I think qqnorm and qqline cannot be applied.
Perhaps you can help?
Ralf
2005 Feb 25
4
Temporal Analysis of variable x; How to select the outlier threshold in R?
For a financial data set with large variance, I'm trying to find the
outlier threshold of one variable "x" over a two year period. I
qqplot(x2001, x2002) and found a normal distribution. The latter part of
the normal distribution did not look linear though. Is there a suitable
method in R to find the outlier threshold of this variable from 2001 and
2002 in R?
2013 Nov 26
4
Unsupported Hardware that works fine?
I recently purchased a set of ASRock Intel i5 MB/CPU combos for a budget
compute cluster. Every time we load up a system and try to boot with a
recent EL6/64 ISO, we get a message that reads:
> This hardware (or a combination thereof) is not supported by CentOS.
For more
> information on supported hardware, plesae refer to
http://www.centos.org/hardware
Not only does the hardware
2004 Sep 22
5
t test problem?
Hello,
I got two sets of data
x=(124738, 128233, 85901, 33806, ...)
y=(25292, 21877, 45498, 63973, ....)
When I did a t test, I got two tail p-value = 0.117, which is not significantly different.
If I changed x, y to log scale, and re-do the t test, I got two tail p-value = 0.042, which is significantly different.
Now I got confused which one is correct. Any help would be very appreciated.
2006 Jul 05
2
p-values
Dear All,
When I run rlm to obtain robust standard errors, my output does not include
p-values. Is there any reason p-values should not be used in this case? Is
there an argument I could use in rlm so that the output does
include p-values?
Thanks in advance,
Celso
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2010 Aug 23
2
Quantile Regression and Goodness of Fit
All -
Does anyone know if there is a method to calculate a goodness-of-fit
statistic for quantile regressions with package quantreg?
Specifically, I'm wondering if anyone has implemented the
goodness-of-fit process developed by Koenker and Machado (1999) for R?
Though I have used package quantreg in the past, I may have overlooked
this function, if it is included.
Citation:
Koenker, R. and
2005 Nov 17
1
Fitdistr()
When using fitdistr() with the exponential, log-normal and beta distributions,
you get the relevent rate, mean, standard deviation, shape1 and shape2 but
you get a number bellow those that are in () and I was wandering what exactly
those numbers represent and how they relate to the data.
Many thanks
Mark Miller