Displaying 20 results from an estimated 6000 matches similar to: "Optim() violates constraints"
2008 Jul 21
1
Control parameter of the optim( ): parscale
Hi everybody,
I am using the L-BFGS-B method of the mle2() function to estimate the values
of 6 parameters. mle2 uses the methods implemented in optim. As I got it
from the descriptions available online, one can use the parscale
parameter to tell R somehow what the values of the estimated parameters
should be . . .
Could somebody please help me understand what one has to do actually with
the
2008 Jul 23
1
mle2(): logarithm of negative pdfs
Hi,
In order to use the mle2-function, one has to define the likelihood function
itself. As we know, the likelihood function is a sum of the logarithm of
probability density functions (pdf). I have implemented myself the pdfs
that I am using. My problem is, that the pdfs values are negative and I
cann't take the logarithm of them in the log-likelihood function.
So how can one take the
2008 Aug 18
2
Call a Fortran subroutine with R: R crashes
Hello,
I am trying to call a FORTRAN subroutine within R and something really
strange happens:
I have a dll-library, that I load with dyn.load('mpbvv.dll'). I have checked
the [Ordinal/Name Pointer] Table for the function within the library that I
want to call - it is there (objdump - p mpbvv.dll).
Then, I have written an R-wrapper to call the FORTRAN subroutine, which
works fine. SInce
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
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,
2009 Nov 04
1
compute maximum likelihood estimator for a multinomial function
Hi there
I am trying to learn how to compute mle in R for a multinomial negative
log likelihood function.
I am using for this the book by B. Bolker "Ecological models and data in
R", chapter 6: "Likelihood an all that". But he has no example for
multinomial functions.
What I did is the following:
I first defined a function for the negative log likelihood:
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 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
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
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
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
2012 Jan 12
2
Function accepted by optim but not mle2 (?)
Dear Sir/ Madam,
I'm having trouble de-bugging the following - which works perfectly
well with optim or optimx - but not with mle2.
I'd be really grateful if someone could show me what is wrong. Many
thanks in advance. JSC:
gompertz<- function (x,t=data)
{
a3<-x[1]
b3<-x[2]
shift<-data[1]
h.t<-a3*exp(b3*(t-shift))
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 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)
2012 Feb 01
3
Probit regression with limited parameter space
Dear R helpers,
I need to estimate a probit model with box constraints placed on several of
the model parameters. I have the following two questions:
1) How are the standard errors calclulated in glm
(family=binomial(link="probit")? I ran a typical probit model using the
glm probit link and the nlminb function with my own coding of the
loglikehood, separately. As nlminb does not
2008 Sep 19
0
panel data analysis possible with mle2 (bbmle)?
Dear R community,
I want to estimate coefficients in a (non-linear) system of equations using
'mle2' from the "bbmle" package. Right now the whole data is read in as just
one long time series, when it's actually 9 cross sections with 30 observations
each. I would like to be able to test and correct for autocorrelation but
haven't found a way to do this in this package.
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
2009 Aug 10
1
model.matrix evaluation challenges
I am having difficulty with evaluation/environment construction
for a formula to be evaluated by model.matrix(). Basically, I
want to construct a model matrix that first looks in "newdata"
for the values of the model parameters, then in "object at data".
Here's what I've tried:
1. model.matrix(~f,data=c(newdata,object at data)) -- fails because
something (terms()?)
2009 Aug 31
2
interactions and stall or memory shortage
Hello,
After putting together interaction code that worked for a single pair of
interactions, when I try to evaluate two pairs of interactions(
flowers*gopher, flowers*rockiness) my computer runs out of memory, and the
larger desktop I use just doesn't go anywhere after about 20 minutes.
Is it really that big a calculation?
to start:
mle2(minuslogl = Lily_sum$seedlings ~ dnbinom(mu = a,