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)
| x | vector of binomial random variables. |
|---|---|
| freq | vector of frequencies. |
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.
$$0 < mode=c < 1$$ $$x = 0,1,2,...$$ $$freq \ge 0$$
NOTE : If input parameters are not in given domain conditions necessary error messages will be provided to go further.
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.
Available at: http://www.sciencedomain.org/abstract.php?iid=699&id=6&aid=6427.
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 # }