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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

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

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

Hi, I am using the mle2 method of the package 'bbmle'. The method is calling as far as I understood it the optim method "L-BFGS-B" (this is the method I use). The latter one allows the user to impose box constraints on the variables, i.e. to give lower and upper bounds. It is important that the initial values satisfy the constraints. In my problem, it is the case. I do not know

Dear all, I need your advice since I am looking for an implementation of the parabolic cylinder function in R. I found implemantations of the hypergemetric functions (the Whittaker and the confluent hypogeometric functions) in the package fAsianOptions but the parabolic cylinder function was unfortunately not there. Do you know of such implementation? Thank you very much for your advice.