ML.k: Maximum likelihood algorithm for determining the binomial...

In asbio: A Collection of Statistical Tools for Biologists

Maximum likelihood algorithm for determining the binomial dispersal coefficient

Description

The function uses the maximum likelihood method described by Bliss and R. A. Fisher (1953) to determine maximum likelihood estimates for the binomial parameters m (the mean) and k (a parameter describing aggregation/dispersion).

Usage

ML.k(f, x, res = 1e-06)

Arguments

f	A vector of frequencies for objects in x (must be integers).
x	A vector of counts, must be sequential integers.
res	Resolution for the ML estimator.

Value

Returns a list with two items

k	The negative binomial dispersion parameter, k
m	The negative binomial distribution mean, m

Note

The program is slow at the current resolution. Later iterations will use linear interpolation, or Fortran loops, or both.

Author(s)

Ken Aho

References

Bliss, C. I., and R. A. Fisher (1953) Fitting the negative binomial distribution to biological data. Biometrics 9: 176-200.

See Also

dnbinom

Examples

mites <- seq(0, 8)
freq <- c(70, 38, 17, 10, 9, 3, 2, 1, 0)
ML.k(freq, mites) 

asbio documentation built on May 29, 2024, 5:57 a.m.