Displaying 20 results from an estimated 11000 matches similar to: "mle() and with()"
2004 Jun 10
1
overhaul of mle
So, I've embarked on my threatened modifications to the mle subset
of the stats4 package. Most of what I've done so far has *not* been
adding the slick formula interface, but rather making it work properly
and reasonably robustly with real mle problems -- especially ones
involving reasonably complex fixed and default parameter sets.
Some of what I've done breaks backward
2007 Oct 24
1
vectorized mle / optim
Hi the list,
I would need some advice on something that looks like a FAQ: the
possibility of providing vectors to optim() function.
Here is a stupid and short example summarizing the problem:
-------------------------------- example 1 ------------ 8<
----------------------
library(stats4)
data <- rnorm(100,0,1)
lik1 <- function(m, v, data) {
N <- length(data)
lik.mean <-
2012 Jul 05
3
Maximum Likelihood Estimation Poisson distribution mle {stats4}
Hi everyone!
I am using the mle {stats4} to estimate the parameters of distributions by
MLE method. I have a problem with the examples they provided with the
mle{stats4} html files. Please check the example and my question below!
*Here is the mle html help file *
http://stat.ethz.ch/R-manual/R-devel/library/stats4/html/mle.html
http://stat.ethz.ch/R-manual/R-devel/library/stats4/html/mle.html
2006 Jan 19
1
nls profiling with algorithm="port" may violate bounds (PR#8508)
[posted to R-devel, no discussion:
resubmitting it as a bug, just so it gets
logged appropriately]
Sorry to report further difficulties with
nls and profiling and constraints ... the problem
this time (which I didn't check for in my last
round of testing) is that the nls profiler doesn't
seem to respect constraints that have been
set when using the port algorithm.
See test code
2011 May 23
6
Reading Data from mle into excel?
Hi there,
I ran the following code:
vols=read.csv(file="C:/Documents and Settings/Hugh/My Documents/PhD/Swaption
vols.csv"
, header=TRUE, sep=",")
X<-ts(vols[,2])
#X
dcOU<-function(x,t,x0,theta,log=FALSE){
Ex<-theta[1]/theta[2]+(x0-theta[1]/theta[2])*exp(-theta[2]*t)
Vx<-theta[3]^2*(1-exp(-2*theta[2]*t))/(2*theta[2])
dnorm(x,mean=Ex,sd=sqrt(Vx),log=log)
}
2005 Jul 21
1
About object of class mle returned by user defined functions
Hi,
There is something I don't get with object of class "mle" returned by a
function I wrote. More precisely it's about the behaviour of method
"confint" and "profile" applied to these object.
I've written a short function (see below) whose arguments are:
1) A univariate sample (arising from a gamma, log-normal or whatever).
2) A character string
2008 Mar 11
1
messages from mle function
Dears useRs,
I am using the mle function but this gives me the follow erros that I
don't understand. Perhaps there is someone that can help me.
thank you for you atention.
Bernardo.
> erizo <- read.csv("Datos_Stokes_1.csv", header = TRUE)
> head(erizo)
EDAD TALLA
1 0 7.7
2 1 14.5
3 1 16.9
4 1 13.2
5 1 24.4
6 1 22.5
> TAN <-
2007 Aug 13
1
[Fwd: behavior of L-BFGS-B with trivial function triggers bug in stats4::mle]
I sent this in first on 30 July. Now that UseR! is over I'm trying again
(slightly extended version from last time).
With R 2.5.1 or R 2.6.0 (2007-08-04 r42421)
"L-BFGS-B" behaves differently from all of the
other optim() methods, which return the value of the function
when they are given a trivial function (i.e., one with no
variable arguments) to optimize. This is not
a bug in
2006 Jun 23
1
How to use mle or similar with integrate?
Hi
I have the following formula (I hope it is clear - if no, I can try to
do better the next time)
h(x, a, b) =
integral(0 to pi/2)
(
(
integral(D/sin(alpha) to Inf)
(
(
f(x, a, b)
)
dx
)
dalpha
)
and I want to do an mle with it.
I know how to use mle() and I also know about integrate(). My problem is
to give the parameter values a and b to the
2009 Apr 08
3
MLE for bimodal distribution
Hello everyone,
I'm trying to use mle from package stats4 to fit a bi/multi-modal
distribution to some data, but I have some problems with it.
Here's what I'm doing (for a bimodal distribution):
# Build some fake binormally distributed data, the procedure fails also with
real data, so the problem isn't here
data = c(rnorm(1000, 3, 0.5), rnorm(500, 5, 0.3))
# Just to check
2007 Apr 09
1
R:Maximum likelihood estimation using BHHH and BFGS
Dear R users,
I am new to R. I would like to find *maximum likelihood estimators for psi
and alpha* based on the following *log likelihood function*, c is
consumption data comprising 148 entries:
fn<-function(c,psi,alpha)
{
s1<-sum(for(i in 1:n){(c[i]-(psi^(-1/alpha)*(lag(c[i],-1))))^2*
(lag(c[i],-1)^((-2)*(alpha+1))
)});
s2<- sum(for(m in 1:n){log(lag(c[m],-1)^(((2)*alpha)+2))});
2008 Sep 04
1
pass data to log-likelihood function
Hi there,
When I do bootstrap on a maximum likelihood estimation, I try the
following code, however, I get error:
Error in minuslogl(alpha = 0, beta = 0) : object "x" not found
It seems that mle() only get data from workspace, other than the
boot.fun().
My question is how to pass the data to mle() in my case.
I really appreciated to any suggestions.
Best wishes,
Jinsong
2005 Sep 06
2
(no subject)
my problem actually arised with fitting the data to the weibulldistribution,
where it is hard to see, if the proposed parameterestimates make sense.
data1:2743;4678;21427;6194;10286;1505;12811;2161;6853;2625;14542;694;11491;
?? ?? ?? ?? ?? 14924;28640;17097;2136;5308;3477;91301;11488;3860;64114;14334
how am I supposed to know what starting values i have to take?
i get different
2006 Jun 02
2
Problem with mle
R 2.3.0
Linux, SuSE 10.0
Hi
I have two problems with mle - probably I am using it the wrong way so
please let me know.
I want to fit different distributions to an observed count of seeds and
in the next step use AIC or BIC to identify the best distribution.
But when I run the script below (which is part of my original script), I
get one error message for the first call of mle:
Error in
2007 Dec 20
3
mle
Dear all,
I'm trying to estimate the parameters of a special case of a poisson
model, where the specified equation has an integral and several fixed
parameters.
I think that the MLE command in STATS4 package could be a good choice,
but it's a little complicated. I've got some problems with the offset
and I don't understand some of the functions. Do you know where can I
find some
2008 May 08
3
MLE for noncentral t distribution
I have a data with 236 observations. After plotting the histogram, I found that it looks like non-central t distribution. I would like to get MLE for mu and df.
I found an example to find MLE for gamma distribution from "fitting distributions with R":
library(stats4) ## loading package stats4
ll<-function(lambda,alfa) {n<-200
x<-x.gam
2010 Jul 31
2
Is profile.mle flexible enough?
Hi the list,
I am experiencing several issues with profile.mle (and consequently with
confint.mle) (stat4 version 2.9.2), and I have to spend a lot of time to
find workarounds to what looks like interface bugs. I would be glad to
get feedback from experienced users to know if I am really asking too
much or if there is room for improvement.
* Problem #1 with fixed parameters. I can't
2018 May 28
2
to R Core T: mle function in 32bits not respecting the constrain
I have an issue using mle in versions of 32 bits.
I am writing a package which I want to submit to the CRAN.
When doing the check, there is an example that has an error running in the
32 bits version.
The problem comes from the mle function, using it with a lower constrain.
In 64 bits version it works fine but when I put it in the R 32 bits it
fails. (same numbers, all equal!)
The call is:
2005 May 31
1
Solved: linear regression example using MLE using optim()
Thanks to Gabor for setting me right. My code is as follows. I found
it useful for learning optim(), and you might find it similarly
useful. I will be most grateful if you can guide me on how to do this
better. Should one be using optim() or stats4::mle?
set.seed(101) # For replicability
# Setup problem
X <- cbind(1, runif(100))
theta.true <- c(2,3,1)
y <- X
2006 Oct 24
0
Variables ordering problem in mle() (PR#9313)
Full_Name: S?bastien Villemot
Version: 2.4.0
OS: Debian testing
Submission from: (NULL) (62.212.121.128)
Hi,
In the mle() function of the stats4 package, there is a bug in the ordering of
the variables given in the 'start' argument.
By just changing the order of the variables listed in the 'start' list (the
initialization values), it is possible to obtain different estimation