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)
aGIIBin <- bbmle::coef(parameters)[1] #assigning the estimated a
bGIIBin <- bbmle::coef(parameters)[2] #assigning the estimated b
#fitting when the random variable,frequencies,shape parameter values are given.
results <- fitGrassiaIIBin(No.D.D,Obs.fre.1,aGIIBin,bGIIBin)
results
#extracting the expected frequencies
fitted(results)
#extracting the residuals
residuals(results)
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