I am trying to fit the chi-squared distribution to a set of data using the
fitdistr function found in the MASS4 library, the data set is called ONES3, I
have loaded it using the command
ONES3-read.table(ONES3.pdf,header=TRUE,na=NA)
I print out the dataset ONES3 to the screen to make
I assume that you want to do the fitdistr on one of the columns of the
dataframe that you have read in. What does 'str(ONES3)' show? If the
data is in the first column, try:
fitdistr(ONES3[[1]],chi-squared)
On 9/9/07, Terence Broderick [EMAIL PROTECTED] wrote:
I am trying to fit the
On Sat, 23 Sep 2006, Luca Telloli wrote:
Hello R-Users,
I'm new to R so I apologize in advance for any big mistake I might
be doing. I'm trying to fit a set of samples with some probabilistic
curve, and I have an important question to ask; in particular I have
some data, from which I
Hello R-Users,
I'm new to R so I apologize in advance for any big mistake I might
be doing. I'm trying to fit a set of samples with some probabilistic
curve, and I have an important question to ask; in particular I have
some data, from which I calculate manually the CDF, and then I
At 09:35 AM 2/10/2006, Gregor Gorjanc wrote:
Hello!
I would like to get MLE for parameter lambda of Poisson distribution. I
can use fitdistr() for this. After looking a bit into the code of this
function I can see that value for lambda and its standard error is
estimated via
estimate - mean(x)
Bernardo Rangel tura wrote:
At 09:35 AM 2/10/2006, Gregor Gorjanc wrote:
Hello!
I would like to get MLE for parameter lambda of Poisson distribution. I
can use fitdistr() for this. After looking a bit into the code of this
function I can see that value for lambda and its standard error is
Hello!
I would like to get MLE for parameter lambda of Poisson distribution. I
can use fitdistr() for this. After looking a bit into the code of this
function I can see that value for lambda and its standard error is
estimated via
estimate - mean(x)
sds - sqrt(estimate/n)
Is this MLE? With
Gregor Gorjanc [EMAIL PROTECTED] writes:
Hello!
I would like to get MLE for parameter lambda of Poisson distribution. I
can use fitdistr() for this. After looking a bit into the code of this
function I can see that value for lambda and its standard error is
estimated via
estimate -
Peter Dalgaard wrote:
Gregor Gorjanc [EMAIL PROTECTED] writes:
Hello!
I would like to get MLE for parameter lambda of Poisson distribution. I
can use fitdistr() for this. After looking a bit into the code of this
function I can see that value for lambda and its standard error is
estimated
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
(0.89052006) (0.01948648)
^^^ ^^^
From: Mark Miller mmiller at nassp.uct.ac.za
Subject: [R] Fitdistr()
Newsgroups: gmane.comp.lang.r.general
Date: 2005-11-17 07:58:10 GMT (4 hours and 2 minutes
ago)
When using fitdistr() with the exponential, log-normal
and beta distributions,
you get
Hello,
I have detailed (with pictures and whatnot) my question on my weblog at
http://www.cs-ed.org/blogs/mjadud/archives/2005/05/a_question_abou.html
The short version of the question is this:
When I ask 'fitdistr' to try and fit my distribution as a weibull
distribution, it comes up with
{BCC'ed to VR's maintainer}
Carsten == Carsten Steinhoff [EMAIL PROTECTED]
on Tue, 5 Apr 2005 17:31:04 +0200 writes:
Carsten Hi all, I'm using the function fitdistr (library
Carsten MASS) to fit a distribution to given data. What I
Carsten have to do further, is getting
Hi all,
I'm using the function fitdistr (library MASS) to fit a distribution to
given data.
What I have to do further, is getting the log-Likelihood-Value from this
estimation.
Is there any simple possibility to realize it?
Regards, Carsten
__
Thanks, your advice worked. I don't have much experience with maths, and
therefore tried to stay away from dealing with optimization, but going
down to this level opens a lot of possibilities. For the record, the
code I used, as you suggested:
###
shape - mean(data)^2/var(data)
scale
I'm sorry, but I don't have time to read all your code. However,
I saw that you tested for x alpha in your Pareto distribution
example. Have you considered reparameterizing to estimate log.del =
log(alpha-min(x))? Pass log.del as part of the vector of parameters to
estimate, then
Thanks for the help, the wrapper function was very useful. I managed to
solve the problem using Spencer Graves' suggestion. I am analyzing the
interarrival times between HTTP packets on a campus network. The dataset
actually has more than 14 Million entries! It represents the traffic
generated by
Are you interested in turning that into a monitor, processing each
day's data sequentially or even each entry as it arrived? If yes, you
may wish to evaluate the Foundations of Monitoring documents
downloadable from www.prodsyse.com. If you have any questions about
that, I might be able
Dear R Users,
I am trying to obtain a best-fit analytic distribution for a dataset
with 11535459 entries. The data range in value from 1 to 3. I
use: fitdistr(data, gamma) to obtain mle's for the parameters.
I get the following error:
Error in optim(start, mylogfn, x = x, hessian =
In my experience, the most likely cause of this problem is that
optim may try to test nonpositive values for shape or scale. I avoid
this situation by programming the log(likelihood) in terms of log(shape)
and log(scale) as follows:
gammaLoglik -
+ function(x, logShape, logScale,
Spencer Graves's suggestion of using shape and scale parameters on a log
scale is a good one.
To do specifically what you want (check values for which the objective
function is called and see what happens) you can do the following
(untested!), which makes a local copy of dgamma that you
PS. 11 MILLION entries??
On Tue, 30 Sep 2003, Ben Bolker wrote:
Spencer Graves's suggestion of using shape and scale parameters on a log
scale is a good one.
To do specifically what you want (check values for which the objective
function is called and see what happens) you can
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