The function will estimate the mode value using the maximum log likelihood method for the Triangular Binomial Distribution when the binomial random variables and corresponding frequencies are given.

EstMLETriBin(x,freq)

## Arguments

x vector of binomial random variables. vector of frequencies.

## Value

The output of EstMLETriBin will produce the classes of ml and mlTB format consisting

min Negative log likelihood value.

mode Estimated mode value.

AIC AIC value.

call the inputs for the function.

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

## Details

$$0 < mode=c < 1$$ $$x = 0,1,2,...$$ $$freq \ge 0$$

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

## References

Horsnell, G. (1957). Economic acceptance sampling schemes. Journal of the Royal Statistical Society, Series A, 120:148-191.

Karlis, D. & Xekalaki, E., 2008. The Polygonal Distribution. In Advances in Mathematical and Statistical Modeling. Boston: Birkhuser Boston, pp. 21-33.

Available at: http://dx.doi.org/10.1007/978-0-8176-4626-4_2.

Okagbue, H. et al., 2014. Using the Average of the Extreme Values of a Triangular Distribution for a Transformation, and Its Approximant via the Continuous Uniform Distribution. British Journal of Mathematics & Computer Science, 4(24), pp.3497-3507.

## 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 mode value and extracting the mode value
results <- EstMLETriBin(No.D.D,Obs.fre.1)

# extract the mode value and summary
coef(results)
summary(results)

AIC(results)  #show the AIC value

# }