EstMLEAddBin: Estimating the probability of success and alpha for Additive...

In fitODBOD: Modeling Over Dispersed Binomial Outcome Data Using BMD and ABD

Estimating the probability of success and alpha for Additive Binomial Distribution

Description

The function will estimate the probability of success and alpha using the maximum log likelihood method for the Additive Binomial distribution when the binomial random variables and corresponding frequencies are given.

Usage

EstMLEAddBin(x,freq)

Arguments

x	vector of binomial random variables.
freq	vector of frequencies.

Details

freq \ge 0

x = 0,1,2,..

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

Value

The output of EstMLEAddBin will produce the class mlAB and ml with a list consisting

min Negative Log Likelihood value.

p estimated probability of success.

alpha estimated alpha parameter.

AIC AIC value.

call the inputs for the function.

Methods print, summary, coef and AIC can be used to extract specific outputs.

References

\insertRef

johnson2005univariatefitODBOD \insertRefkupper1978usefitODBOD \insertRefpaul1985threefitODBOD \insertRefmorel2012overdispersionfitODBOD

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

## Not run: 
#estimating the probability value and alpha value
results <- EstMLEAddBin(No.D.D,Obs.fre.1)

#printing the summary of results
summary(results)

#extracting the estimated parameters
coef(results)

## End(Not run)

fitODBOD documentation built on June 28, 2024, 9:06 a.m.