R/Gamma.R
EstMLEGrassiaIIBin.Rd
The function will estimate the shape parameters using the maximum log likelihood method for the Grassia II Binomial distribution when the binomial random variables and corresponding frequencies are given.
EstMLEGrassiaIIBin(x,freq,a,b,...)
x | vector of binomial random variables. |
---|---|
freq | vector of frequencies. |
a | single value for shape parameter a. |
b | single value for shape parameter b. |
... | mle2 function inputs except data and estimating parameter. |
EstMLEGrassiaIIBin
here is used as a wrapper for the mle2
function of bbmle package
therefore output is of class of mle2.
$$0 < a,b$$ $$x = 0,1,2,...$$ $$freq \ge 0$$
NOTE : If input parameters are not in given domain conditions necessary error messages will be provided to go further.
Grassia, A., 1977. On a family of distributions with argument between 0 and 1 obtained by transformation of the gamma and derived compound distributions. Australian Journal of Statistics, 19(2), pp.108-114.
No.D.D <- 0:7 #assigning the random variables Obs.fre.1 <- c(47,54,43,40,40,41,39,95) #assigning the corresponding frequencies #estimating the parameters using maximum log likelihood value and assigning it parameters <- EstMLEGrassiaIIBin(x=No.D.D,freq=Obs.fre.1,a=0.1,b=0.1) bbmle::coef(parameters) #extracting the parameters#> a b #> 0.7285048 2.0251467