The function will estimate the covariance, alpha and beta parameter values using the maximum log likelihood method for the Beta-Correlated Binomial distribution when the binomial random variables and corresponding frequencies are given.

EstMLEBetaCorrBin(x,freq,cov,a,b,...)

Arguments

x

vector of binomial random variables.

freq

vector of frequencies.

cov

single value for covariance.

a

single value for alpha parameter.

b

single value for beta parameter.

...

mle2 function inputs except data and estimating parameter.

Value

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

Details

$$x = 0,1,2,...$$ $$freq \ge 0$$ $$-\infty < cov < +\infty$$ $$0 < a,b$$

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

References

Paul, S.R., 1985. A three-parameter generalization of the binomial distribution. Communications in Statistics - Theory and Methods, 14(6), pp.1497-1506.

Available at: http://www.tandfonline.com/doi/abs/10.1080/03610928508828990 .

See also

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 <- EstMLEBetaCorrBin(x=No.D.D,freq=Obs.fre.1,cov=0.0050,a=10,b=10) bbmle::coef(parameters) #extracting the parameters
#> cov a b #> 0.07068406 3.19944807 2.63292837