Displaying 20 results from an estimated 2000 matches similar to: "compute maximum likelihood estimator for a multinomial function"
2010 Feb 12
1
using mle2 for multinomial model optimization
Hi there
I'm trying to find the mle fo a multinomial model ->*L(N,h,S?x)*. There
is only *N* I want to estimate, which is used in the number of successes
for the last cell probability. These successes are given by:
p^(N-x1-x2-...xi)
All the other parameters (i.e. h and S) I know from somewhere else.
Here is what I've tried to do so far for a imaginary data set:
2007 Mar 30
1
faster computation of cumulative multinomial distribution
Dear list members,
I have a series of /unequal/ probabilities [p1,p2,...,pk], describing
mutually exclusive events, and a "remainder" class with a probability
p0=1-p1-p2-....-pk, and need to calculate, for a given number of trials
t>=k, the combined probability that each of the classes 1...k contains
at least 1 "event" (the remainder class may be empty).
To me this reaks
2007 Mar 05
3
Mixed effects multinomial regression and meta-analysis
R Experts:
I am conducting a meta-analysis where the effect measures to be pooled
are simple proportions. For example, consider this data from
Fleiss/Levin/Paik's Statistical methods for rates and proportions (2003,
p189) on smokers:
Study N Event P(Event)
1 86 83 0.965
2 93 90 0.968
3 136 129 0.949
4 82 70 0.854
Total
2010 Mar 09
1
using near-zero probabilities in optimization
Hi there
I am using mle2 for a multinomial likelihood optimization problem. My
function works fine when I'm using simulated data, however my cell
probabilities of the true data for the multinomial likelihood are
sometimes very small (in some cases <0.00...) and the estimated point
estimates fit the true vlaues quite poorly. Is there a way how to handle
near zero probabilities in
2011 Oct 17
1
simultaneously maximizing two independent log likelihood functions using mle2
Hello,
I have a log likelihood function that I was able to optimize using
mle2. I have two years of the data used to fit the function and I would
like to fit both years simultaneously to test if the model parameter
estimates differ between years, using likelihood ratio tests and AIC.
Can anyone give advice on how to do this?
My likelihood functions are long so I'll use the tadpole
2012 Oct 05
2
problem with convergence in mle2/optim function
Hello R Help,
I am trying solve an MLE convergence problem: I would like to estimate
four parameters, p1, p2, mu1, mu2, which relate to the probabilities,
P1, P2, P3, of a multinomial (trinomial) distribution. I am using the
mle2() function and feeding it a time series dataset composed of four
columns: time point, number of successes in category 1, number of
successes in category 2, and
2012 Nov 11
1
maximum likelihood estimation in R
I want to find ML estimates of a model using mle2 in bbmle package. When I
insert new parameters (for new covariates) in model the log-likelihood value
does not change and the estimated value is exactly the initial value that I
determined. What's the problem? This is the code and the result:
As you see the estimated values for b2 , b3 and b4 are the initial values of
them. The
2012 Jul 30
1
confusion over S3/S4 importing
Can anyone help me figure out the right way to import a method that is
defined as S3 in one package and S4 in another?
Specifically:
profile() is defined as an S3 method in the stats package:
function (fitted, ...)
UseMethod("profile")
<bytecode: 0xa4cd6e8>
<environment: namespace:stats>
In stats4 it is defined as an S4 method:
stats4:::profile
standardGeneric for
2012 Nov 25
5
bbmle "Warning: optimization did not converge"
I am using the Ben bolker's R package "bbmle" to estimate the parameters of a
binomial mixture distribution via Maximum Likelihood Method. For some data
sets, I got the following warning messages:
*Warning: optimization did not converge (code 1: )
There were 50 or more warnings (use warnings() to see the first 50)*
Also, warnings() results the following:
*In 0:(n - x) : numerical
2007 Jan 05
1
Efficient multinom probs
Dear R-helpers,
I need to compute probabilties of multinomial observations, eg by doing the
following:
y=sample(1:3,15,1)
prob=matrix(runif(45),15)
prob=prob/rowSums(prob)
diag(prob[,y])
However, my question is whether this is the most efficient way to do this.
In the call prob[,y] a whole matrix is computed which seems a bit of a
waste.
Is there maybe a vectorized version of dmultinom which
2009 Feb 01
2
Extracting Coefficients and Such from mle2 Output
The mle2 function (bbmle library) gives an example something like the
following in its help page. How do I access the coefficients, standard
errors, etc in the summary of "a"?
> x <- 0:10
> y <- c(26, 17, 13, 12, 20, 5, 9, 8, 5, 4, 8)
> LL <- function(ymax=15, xhalf=6)
+ -sum(stats::dpois(y, lambda=ymax/(1+x/xhalf), log=TRUE))
> a <- mle2(LL,
2012 Jul 11
0
declaring negative log likelihood of a distribution
Hi everyone!
I already posted
http://r.789695.n4.nabble.com/Declaring-a-density-function-with-for-loop-td4635699.html
a question on finding density values of a new Binomial like distribution
which has the following pmf:
http://r.789695.n4.nabble.com/file/n4636134/kb.png
Thank fully
http://r.789695.n4.nabble.com/template/NamlServlet.jtp?macro=user_nodes&user=124474
Berend Hasselman and
2008 Sep 10
1
using function instead of formula in plm
Hi all,
I am trying to use plm to estimate coefficients in a model consisting of a system of equations. So far I used mle2 from the package "bbmle", but now I need to test for autocorrelation and mle2 does not provide for the necessary tests. mle2 needs a function as input that might as well consist of many different equations. plm however requires an object of class formula that needs
2008 Nov 19
1
mle2 simple question - sigma?
I'm trying to get started with maximum likelihood estimation with a
simple regression equivalent out of Bolker (Ecological Models and Data
in R, p302).
With this code:
#Basic example regression
library(bbmle)
RegData<-data.frame(c(0.3,0.9,0.6),c(1.7,1.1,1.5))
names(RegData)<-c("x", "y")
linregfun = function(a,b,sigma) {
Y.pred = a+b*x
2012 Apr 18
1
error estimating parameters with mle2
Hi all,
When I try to estimate the functional response of the Rogers type I
equation (for the mle2 you need the package bbmle):
> RogersIbinom <- function(N0,attackR2_B,u_B) {attackR2_B+u_B*N0}
> RogersI_B <-
mle2(FR~dbinom(size=N0,prob=RogersIbinom(N0,attackR2_B,u_B)/N0),start=list(attackR2_B=4.5,u_B=0.16),method="Nelder-Mead",data=data5)
I get following error message
2019 Apr 08
1
debian testing: Problems with R function vignette()
Hola!
I am on debian testing, all updates up to date. I am running R via emacs
and ess, so I canot know if this is an R or emacs/ess problem. What
happens is that I want to read an vignette, and calls something like
vignette("mle2", package="bbmle")
the pdf file opens (for me in Foxit reader), no problem, but then emacs
starts to spew a lot of spam, interfering with the
2009 Aug 01
4
Likelihood Function for Multinomial Logistic Regression and its partial derivatives
Hi,
I would like to apply the L-BFGS optimization algorithm to compute the MLE
of a multilevel multinomial Logistic Regression.
The likelihood formula for this model has as one of the summands the formula
for computing the likelihood of an ordinary (single-level) multinomial logit
regression. So I would basically need the R implementation for this formula.
The L-BFGS algorithm also requires
2011 Feb 11
2
fitdistr question
Hello,
I tried to fit a poisson distribution but looking at the function
fitdistr() it does not optimize lambda but simply estimates the mean
of the data and returns it as lambda. I'm a bit confused because I was
expecting an optimization of this parameter to gain a good fit...
If I would use mle() of stats4 package or mle2() of bbmle package, I
would have to write the function by myself
2012 Oct 11
2
model selection with spg and AIC (or, convert list to fitted model object)
Dear R Help,
I have two nested negative log-likelihood functions that I am optimizing
with the spg function [BB package]. I would like to perform model
selection on these two objective functions using AIC (and possibly
anova() too). However, the spg() function returns a list and I need a
fitted model object for AIC(), ICtab() [bbmle package], or anova().
How can I perform AIC-based model
2012 Apr 19
1
non-numeric argument in mle2
Hi all,
I have some problems with the mle2 function
> RogersIIbinom <- function(N0,attackR3_B,Th3_B)
{N0-lambertW(attackR3_B*Th3_B*N0*exp(-attackR3_B*(24-Th3_B*N0)))/(attackR3_B*Th3_B)}
> RogersII_B <-
mle2(FR~dbinom(size=N0,prob=RogersIIbinom(N0,attackR3_B,Th3_B)/N0),start=list(attackR3_B=1.5,Th3_B=0.04),method="Nelder-Mead",data=dat)
Error in dbinom(x, size, prob, log)