R/BetaCorrBin.R
EstMLEBetaCorrBin.Rd
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,...)
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. |
EstMLEBetaCorrBin
here is used as a wrapper for the mle2
function of bbmle package
therefore output is of class of mle2.
$$x = 0,1,2,...$$ $$freq \ge 0$$ $$-\infty < cov < +\infty$$ $$0 < a,b$$
NOTE : If input parameters are not in given domain conditions necessary error messages will be provided to go further.
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 .
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