Displaying 20 results from an estimated 100 matches similar to: "Zipf random number generation"
2008 Dec 27
1
Zipf fitting using R
Dear R-users,
I am new to R and would like to use it for fitting the zipf distribution to
some numeric data that I have. Here's the snippet that I use:
library(VGAM)
X <- read.table(file("~\\mydata.txt", encoding="latin1"))
w <- as.vector(t((X[2])))
w <- w/sum(w)
y <- (1:length(w))
fit = vglm (y ~ 1, zipf, tra=TRUE, weight=w)
zipf(N=NULL,
2010 Oct 11
1
plotting Zipf and Zipf-Mandelbrot curves in R
Using R, I plotted a log-log plot of the frequencies in the Brown Corpus
using
plot(sort(file.tfl$f, decreasing=TRUE), xlab="rank", ylab="frequency",
log="x,y")
However, I would also like to add lines showing the curves for a Zipfian
distribution and for Zipf-Mandelbrot.
I have seen these in many articles that used R in creating graphs.
Thank you!
[[alternative HTML
2005 Jan 25
4
agglomerative coefficient in agnes (cluster)
I haven't read the book, but could anyone explain more
about this parameter?
help(agnes) says that ac measures the amount of
clustering structure found. From the definition given
in help(agnes.object), however, it seems that as long
as
the dissimilarity of the merger in the final step of
the
algorithm is large enough, the ac value will be close
to
1. So what does ac really mean?
Thank
2007 Feb 08
1
Zeta and Zipf distribution
Dear R user,
I want to estimate the parameter of ZETA or/and ZIPF distributions
using R, given a series of integer values. Do you know a package
(similar to MASS) or a function (similar to fitdistr) I can use to
estimate the parameter of these distributions using MLE method?
Otherwise do you know a function (which use MLE method to estimate
distribution parameters) that allow me to specify a
2005 Mar 08
2
The null hypothesis in kpss test (kpss.test())
is that 'x' is level or trend stationary. I did this
> s<-rnorm(1000)
> kpss.test(s)
KPSS Test for Level Stationarity
data: s
KPSS Level = 0.0429, Truncation lag parameter = 7,
p-value = 0.1
Warning message:
p-value greater than printed p-value in:
kpss.test(s)
My question is whether p=0.1 is a good number to
reject
N0? On the other hand, I have a
2005 Mar 09
1
about kpss.test()
Hi All,
First of all, could you tell me what the "KPSS Level"
in the output of the test means?
I have a series, x, of periodic data and tried
kpss.test() on it to verify its stationarity. The
tests
gave me the p-value above 0.1. Since the null
hypothesis N0 is that the series _is_ stationary, this
means that I cannot reject N0. But the series does
look
periodic!
So does all this
2006 Feb 18
1
truncated negative binomial using rnegbin
Dear R users,
I'm wanting to sample from the negative binomial distribution using the
rnegbin function from the MASS library to create artificial samples for the
purpose of doing some power calculations. However, I would like to work
with samples that come from a negative binomial distribution that includes
only values greater than or equal to 1 (a truncated negative binomial), and
I
2011 May 04
1
hurdle, simulated power
Hi all--
We are planning an intervention study for adolescent alcohol use, and I
am planning to use simulations based on a hurdle model (using the
hurdle() function in package pscl) for sample size estimation.
The simulation code and power code are below -- note that at the moment
the "power" code is just returning the coefficients, as something isn't
working quite right.
The
2004 Feb 10
1
generate random sample from ZINB
I want to generate 1,000 random samples of sample size=1,000 from ZINB.
I know there is a rnegbin() to generate random samples from NB, and I know
I can use
the following process:
do i=1 to 1000
n=0
do i=1 to 1000
if runi(1)>0.1 then x(i) = 0; else
x(i)=rnegbin();
n=n+1;
if n>1000 then stop;
end;
output;
end;
Anybody can help me out with the R code?
Thanks very much ahead of time.
2012 Mar 31
2
A introductory question about Zips law (Newbie to statistics)
Hi everyone.
Newbie to statistics.
I have 40 matrices of ~400 values. how may I determine whether the
distribution follows zips law?
response <-sample (1:20,400*4, replace= TRUE)
Thank you vry much.
--
View this message in context: http://r.789695.n4.nabble.com/A-introductory-question-about-Zips-law-Newbie-to-statistics-tp4521190p4521190.html
Sent from the R help mailing list archive at
2006 Jul 14
2
Negative Binomial: Simulation
Hi R-Users!
I fitted a negative binomial distribution to my count data using the
function glm.nb() and obtained the calculated parameters
theta (dispersion) and mu.
I would like to simulate values from this negative binomial distribution.
Looking at the function rnbinom() I was looking at the relationship
between the two possible parametrizations of the negative binomial and found
that for this
2011 Nov 17
1
How to Fit Inflated Negative Binomial
Dear All,
I am trying to fit some data both as a negative binomial and a zero
inflated binomial.
For the first case, I have no particular problems, see the small snippet
below
library(MASS) #a basic R library
set.seed(123) #to have reproducible results
x4 <- rnegbin(500, mu = 5, theta = 4)
#Now fit and check that we get the right parameters
fd <- fitdistr(x4, "Negative
2005 Mar 03
1
Negative binomial regression for count data
Dear list,
I would like to fit a negative binomial regression model as described in "Byers AL, Allore H, Gill TM, Peduzzi PN., Application of negative binomial modeling for discrete outcomes: a case study in aging research. J Clin Epidemiol. 2003 Jun;56(6):559-64" to my data in which the response is count data. There are also 10 predictors that are count data, and I have also 3
2008 Aug 05
4
Buggy bios, boot of dos image hangs with syslinux, but not with isolinux
Hi
We have a couple of FSC Computers here which seem to have a very strange
bios. I am trying to boot a MS-DOS disk to flash an Scsi Raid
controller.
Since the computer doesn't have a floppy anymore I tried syslinux from
an usb stick. The menu loads fine but I cannot boot disc images with
memdisk on this computer. It works fine on others, of course.
But now comes the weird part, if I use the
2005 Apr 04
1
help with kolmogorov smirnov test
What does 'with ties in' mean?
with some identical elements (par ex., au moins une paire ex-equo)
HTH
____________________
Ken Knoblauch
Inserm U371, Cerveau et Vision
Department of Cognitive Neurosciences
18 avenue du Doyen Lepine
69675 Bron cedex
France
tel: +33 (0)4 72 91 34 77
fax: +33 (0)4 72 91 34 61
portable: 06 84 10 64 10
http://www.lyon.inserm.fr/371/
2012 Oct 19
2
MLE of negative binomial distribution parameters
I need to estimate the parameters for negative binomial distribution (pdf)
using maximun likelihood, I also need to estimate the parameter for the
Poisson by ML, which can be done by hand, but later I need to conduct a
likelihood ratio test between these two distributions and I don't know how
to start! I'm not an expert programmer in R. Please help
--
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2007 Oct 17
2
power law fit with unknown zero
Dear R-helpers
I would like to do a fit of the form: y = a (x+c)**b, where a, b and c
are unknown.
Does anybody know how to do it?
Thanks
Thomas
2011 Feb 04
2
vegan and sweave using xtable
Dear all,
Using:
library(vegan)
data(BCI)
mod <- radfit(BCI[1,])
mod
RAD models, family poisson
No. of species 93, total abundance 448
par1 par2 par3 Deviance AIC BIC
Null 39.5261 315.4362 315.4362
Preemption 0.042797 21.8939 299.8041 302.3367
Lognormal 1.0687 1.0186 25.1528 305.0629 310.1281
2006 Oct 27
0
VGAM package released on CRAN
Dear useRs,
upon request, the VGAM package (currently version 0.7-1) has been
officially released on CRAN (the package has been at my website
http://www.stat.auckland.ac.nz/~yee/VGAM for a number of years now).
VGAM implements a general framework for several classes of
regression models using iteratively reweighted least squares
(IRLS). The key ideas are Fisher scoring, generalized linear
and
2012 Apr 23
2
zipfR help
Hi,
I have a question on generating random variables based on zipf-mandelbrot
distribution.
So when I execute the following lines:
ZM = lnre ("zm", alpha = 2/3, B=0.1)
zmsample = rlnre (ZM, n =100)
zmsample
It generates 100 random values based on a zipf-mandelbrot distribution as
below. But how do I make sure the generated random number is within the
range of 1 - 6000 only? Can I