Maximum likelihood estimation
Yes I'm trying to optimize the parameters a, b, p and lambda where a > 0, b > 0 and 0 < p < 1. I attached the error message that I got when I run mle.
t <- c(1:90) y <- c(5,10,15,20,26,34,36,43,47,49,80,84,108,157,171,183,191,200,204,211,217,226,230,
+ 234,236,240,243,252,254,259,263,264,268,271,277,290,309,324,331,346,367,375,381, + 401,411,414,417,425,430,431,433,435,437,444,446,446,448,451,453,460,463,463,464, + 464,465,465,465,466,467,467,467,468,469,469,469,469,470,472,472,473,473,473,473, + 473,473,473,475,475,475,475)
library(stats4)
fr <- function(a, b, p, lambda){
+ l <- 0.5*(lambda + b*p + (1-p)*(lambda-b)) + l^2 > lambda*b*p + delta <- sqrt(abs(l^2 - b*p*lambda)) + mt <- a/p*(1-exp(-l*t)*cosh(delta*t)-(l-b*p)*exp(-t)*sinh(delta*t)/delta) + logl <- sum(diff(y)*log(diff(mt))-diff(mt)-lfactorial(diff(y))) + return(-logl) + }
mle(start=list(a=12,b=0.01,p=0.5,lambda=0.01),fr, method="L-BFGS-B",
+ lower = c(0.002, 0.002, 0.002, 0.002), upper = c(Inf, Inf, 0.999, Inf),control=list(fnscale=-1)) Error in optim(start, f, method = method, hessian = TRUE, ...) : non-finite finite-difference value [3]
Prof Brian Ripley wrote:
From ?optim
fn: A function to be minimized (or maximized), with first
argument the vector of parameters over which minimization is
to take place. It should return a scalar result.
I think you intended to optimize over c(a,b,p, lambda), so you need to
specify them as a single vector.
You may be making life unnecessarily hard for yourself: see function mle()
in package stats4.
Showing your code without a verbal description of what you are doing nor
the error message you got is less helpful than we need.
On Wed, 3 Sep 2008, toh wrote:
Hi R-experts,
I'm new to R in mle. I tried to do the following but just couldn't get it
right. Hope someone can point out the mistakes. thanks a lot.
t <- c(1:90)
y <-
c(5,10,15,20,26,34,36,43,47,49,80,84,108,157,171,183,191,200,204,211,217,226,230,
234,236,240,243,252,254,259,263,264,268,271,277,290,309,324,331,346,367,375,381,
401,411,414,417,425,430,431,433,435,437,444,446,446,448,451,453,460,463,463,464,
464,465,465,465,466,467,467,467,468,469,469,469,469,470,472,472,473,473,473,473,
473,473,473,475,475,475,475)
fr <- function(a, b, p, lambda){
l <- 0.5*(lambda + b*p + (1-p)*(lambda-b))
l^2 > lambda*b*p
delta <- sqrt(abs(l^2 - b*p*lambda))
mt <- a/p*(1-exp(-l*t)*cosh(delta*t)-(l-b*p)*exp(-t)*sinh(delta*t)/delta)
logl <- sum(diff(y)*log(diff(mt))-diff(mt)-lfactorial(diff(y)))
return(-logl)
}
optim(c(15,0.01,0.5,0.01),fr, method="L-BFGS-B",
lower = c(0.002, 0.002, 0.002, 0.002), upper = c(Inf, Inf, 0.999,
Inf),control=list(fnscale=-1))
--
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______________________________________________ R-help at r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
-- Brian D. Ripley, ripley at stats.ox.ac.uk Professor of Applied Statistics, http://www.stats.ox.ac.uk/~ripley/ University of Oxford, Tel: +44 1865 272861 (self) 1 South Parks Road, +44 1865 272866 (PA) Oxford OX1 3TG, UK Fax: +44 1865 272595
______________________________________________ R-help at r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
View this message in context: http://www.nabble.com/Maximum-likelihood-estimation-tp19304249p19323140.html Sent from the R help mailing list archive at Nabble.com.