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 <- EstMLELMBin(x=No.D.D,freq=Obs.fre.1,p=0.1,phi=.3)
pLMBin=bbmle::coef(parameters)[1] #assigning the estimated probability value
phiLMBin <- bbmle::coef(parameters)[2] #assigning the estimated phi value
#fitting when the random variable,frequencies,probability and phi are given
results <- fitLMBin(No.D.D,Obs.fre.1,pLMBin,phiLMBin)
results
#extracting the AIC value
AIC(results)
#extract fitted values
fitted(results)
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