# [R] How to use mle2 function?

Eric Berger er|cjberger @end|ng |rom gm@||@com
Tue Jun 30 14:06:08 CEST 2020

```I have no problem with the following code:

library(bbmle)
holling <- function( a, b, x ) {
a*x^2 / (b^2 + x^2)
}
A=3261
B=10
X=30
foo <- mle2( minuslogl=holling, start=list(a=A,b=B,x=X) )

foo

# Call:
# mle2(minuslogl = holling, start = list(a = A, b = B, x = X))

# Coefficients:
#            a             b             x
# 3.260044e+03  7.315124e+01 -2.332448e-14

# Log-likelihood: 0

Does this code create a problem for you?

On Tue, Jun 30, 2020 at 3:00 PM Luigi Marongiu <marongiu.luigi using gmail.com> wrote:
>
> Sorry for the typo, but I have the same error if using b instead of h:
> ```
> > O = mle2(minuslogl = holling, start = list(a = A, b = B))
> > Error in minuslogl(a = 3261, b = 10) :
>   argument "x" is missing, with no default
> X = c(8,   24,   39,   63,   89,  115,  153,  196,  242,  287,  344,  408,  473,
>       546,  619,  705,  794,  891,  999, 1096, 1242, 1363, 1506, 1648, 1753,
>       1851, 1987, 2101, 2219, 2328, 2425, 2575, 2646, 2698, 2727, 2771, 2818,
>       2853, 2895, 2926, 2964, 2995, 3025, 3053, 3080, 3102, 3119, 3141, 3152,
>       3159, 3172, 3182, 3196, 3209, 3220, 3231, 3239, 3246, 3252, 3261)
> O = mle2(minuslogl = holling, start = list(a = A, b = B, x = X))
> Error in mle2(minuslogl = holling, start = list(a = A, b = B, x = X)) :
>   some named arguments in 'start' are not arguments to the specified
> log-likelihood function
> ```
> And even if I use the log-likelihood function:
> ```
> O = mle2(minuslogl = nll, start = list(p = c(A, B), n = 57200000, x = X))
> > Error in mle2(minuslogl = nll, start = list(p = c(A, B), n = 57200000,  :
>   some named arguments in 'start' are not arguments to the specified
> log-likelihood function
> ```
>
> On Tue, Jun 30, 2020 at 12:03 PM Eric Berger <ericjberger using gmail.com> wrote:
> >
> > Hi Luigi,
> > I took a quick look.
> >
> > First error:
> > You wrote
> > O = mle2(minuslogl = holling, start = list(a = A, h = B, x = X))
> >
> > it should be b=B  (h is not an argument of holling())
> > The error message gave very precise information!
> >
> > Second error:
> > You wrote
> > O = mle2(minuslogl = nll, start = list(a = A, h = B),   data = list(n
> > = 57200000, k = A))
> > but the arguments to nll() are p,n,k. Setting start to values for a
> > and h causes the function to complain.
> >
> > HTH,
> > Eric
> >
> > On Tue, Jun 30, 2020 at 12:45 PM Luigi Marongiu
> > <marongiu.luigi using gmail.com> wrote:
> > >
> > > Hello,
> > > I would like to optimize the function:
> > > ```
> > > holling = function(a, b, x) {
> > >   y = (a * x^2) / (b^2 + x^2)
> > >   return(y)
> > > }
> > > ```
> > > I am trying to use the function mle2 from bbmle, but how do I need to
> > > feed the data?
> > > If I give `holling` as function to be optimized, passing the starting
> > > values for `a`, `b`, and `x`, I get:
> > > ```
> > > X = 1:60
> > > A = 3261
> > > B = 10
> > > O = mle2(minuslogl = holling, start = list(a = A, h = B, x = X))
> > > > Error in mle2(minuslogl = holling, start = list(a = A, b = B, x = X)) :
> > >   some named arguments in 'start' are not arguments to the specified
> > > log-likelihood function
> > > ```
> > > If I pass the negative log-function (assuming a binomial distribution
> > > of the data, which I am not sure about)
> > > ```
> > > nll = function(p, n, k) {
> > >   # extract parms
> > >   a = p[1]
> > >   h = p[2]
> > >   # calculate probability of attack
> > >   pred = a/(1+a*h*n)
> > >   # calc NLL
> > >   -sum(dbinom(k, prob = pred, size = n, log = TRUE))
> > > }
> > > ```
> > > then I get the same error:
> > > ```
> > > > O = mle2(minuslogl = nll, start = list(a = A, h = B),
> > > +          data = list(n = 57200000, k = A))
> > > Error in mle2(minuslogl = nll, start = list(a = A, h = B), data =
> > > list(n = 57200000,  :
> > >   some named arguments in 'start' are not arguments to the specified
> > > log-likelihood function
> > > ```
> > > but with the disadvantage of working on an assumed function (nll).
> > > How can I optimize the function `holling` properly?
> > > Thank you
> > >
> > >
> > >
> > >
> > > --
> > > Best regards,
> > > Luigi
> > >
> > > ______________________________________________
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