Displaying 6 results from an estimated 6 matches for "minuslogl".

2007 Apr 09

1

R:Maximum likelihood estimation using BHHH and BFGS

...cEcon}*. I have documented some of
my attempts below ((a) package name (b) usage (c) my attempt and
corresponding error). In all humility I apologise for any bad coding, and
ask if anyone can *direct me in finding these estimators*.
Yours sincerely.
*(1a) mle{stats4}
(b) Usage:
mle(minuslogl, start = formals(minuslogl), method = "BFGS",
fixed = list(), ...)
(For this I use the negative of the log-likelihood function,bn)*
*(c) >mle(start=list(psi=1,alpha=0),fn, method="BFGS",fixed=list(c=c))*
Error in optim(start, f, method = method, hessian = TRUE, ...)...

2018 May 28

2

to R Core T: mle function in 32bits not respecting the constrain

...he 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:
*mle(minuslogl = p.est,start = beta,method =
"L-BFGS-B",lower=llim*reduction)*
lower = -0.01570427
The optimizer (optim function in 32 bits) display:
-0.015704 -loglik 48.690236
-0.015704 -loglik 48.690236
-0.017704 -loglik 1.#QNAN0
And it is not respecting the lower constrain.
Could anyone explain...

2018 May 28

0

to R Core T: mle function in 32bits not respecting the constrain

...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:
> *mle(minuslogl = p.est,start = beta,method =
> "L-BFGS-B",lower=llim*reduction)*
> lower = -0.01570427
>
> The optimizer (optim function in 32 bits) display:
> -0.015704 -loglik 48.690236
> -0.015704 -loglik 48.690236
> -0.017704 -loglik 1.#QNAN0
>
> And it is not respectin...

2009 Feb 01

2

Extracting Coefficients and Such from mle2 Output

..."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, fixed=list(xhalf=6))
> summary(a)
Maximum likelihood estimation
Call:
mle2(minuslogl = LL, fixed = list(xhalf = 6))
Coefficients:
Estimate Std. Error z value Pr(z)
ymax 19.2881 1.7115 11.269 < 2.2e-16 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
-2 log L: 60.39244
Tom
--
View this messa...

2006 Oct 29

1

Rmix package and different distributions

hi all!
i want to mix a dataset that is build up from 2 distribution: an
exponential and a normal. I can' figure out how can i use Rmix package
to do the fitting of my data. Pheraps it si the wrong package? any
suggestion?
thanks,
nelson

2011 May 23

0

Error in backSpline.npolySpline(sp) : spline must be monotone

...dcOU
> set.seed(1)
> #X<-sde.sim(model="OU",theta=c(3,1,2),N=10000,delta=1)
> mle(OU.lik,start=list(theta1=1,theta2=1,theta3=1),
+ method="L-BFGS-B",lower=c(-Inf,-Inf,-Inf),upper=c(Inf,Inf,Inf))->fit
> summary(fit)
Maximum likelihood estimation
Call:
mle(minuslogl = OU.lik, start = list(theta1 = 1, theta2 = 1,
theta3 = 1), method = "L-BFGS-B", lower = c(-Inf, -Inf, -Inf),
upper = c(Inf, Inf, Inf))
Coefficients:
Estimate Std. Error
theta1 0.03595581 0.013929892
theta2 4.30910365 1.663781710
theta3 0.02120220 0.004067477
-2 log...