The function will estimate the shape parameters using the maximum log likelihood method for the Gamma Binomial distribution when the binomial random variables and corresponding frequencies are given.

EstMLEGammaBin(x,freq,c,l,...)

Arguments

x

vector of binomial random variables.

freq

vector of frequencies.

c

single value for shape parameter c.

l

single value for shape parameter l.

...

mle2 function inputs except data and estimating parameter.

Value

EstMLEGammaBin here is used as a wrapper for the mle2 function of bbmle package therefore output is of class of mle2.

Details

$$0 < c,l$$ $$x = 0,1,2,...$$ $$freq \ge 0$$

NOTE : If input parameters are not in given domain conditions necessary error messages will be provided to go further.

References

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.

Examples

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 <- EstMLEGammaBin(x=No.D.D,freq=Obs.fre.1,c=0.1,l=0.1) bbmle::coef(parameters) #extracting the parameters
#> c l #> 0.6036041 0.6030764