These functions provide the ability for generating probability function values and cumulative probability function values for the Triangular Binomial distribution.
pTriBin(x,n,mode)
Arguments
x: vector of binomial random variables
n: single value for no of binomial trials
mode: single value for mode
Returns
The output of pTriBin gives cumulative probability function values in vector form.
Details
Mixing unit bounded Triangular distribution with Binomial distribution will create Triangular Binomial distribution. The probability function and cumulative probability function can be constructed and are denoted below.
The cumulative probability function is the summation of probability function values.
Defined as Bc(a,b)=∫0cta−1(1−t)b−1dt is incomplete beta integrals and B(a,b) is the beta function.
NOTE : If input parameters are not in given domain conditions necessary error messages will be provided to go further.
Examples
#plotting the random variables and probability valuescol <- rainbow(7)x <- seq(0.1,0.7,by=0.1)plot(0,0,main="Triangular binomial probability function graph",xlab="Binomial random variable",ylab="Probability function values",xlim = c(0,10),ylim = c(0,.3))for(i in1:7){lines(0:10,dTriBin(0:10,10,x[i])$pdf,col = col[i],lwd=2.85)points(0:10,dTriBin(0:10,10,x[i])$pdf,col = col[i],pch=16)}dTriBin(0:10,10,.4)$pdf #extracting the pdf valuesdTriBin(0:10,10,.4)$mean #extracting the meandTriBin(0:10,10,.4)$var #extracting the variancedTriBin(0:10,10,.4)$over.dis.para #extracting the over dispersion value#plotting the random variables and cumulative probability valuescol <- rainbow(7)x <- seq(0.1,0.7,by=0.1)plot(0,0,main="Triangular binomial probability function graph",xlab="Binomial random variable",ylab="Probability function values",xlim = c(0,10),ylim = c(0,1))for(i in1:7){lines(0:10,pTriBin(0:10,10,x[i]),col = col[i],lwd=2.85)points(0:10,pTriBin(0:10,10,x[i]),col = col[i],pch=16)}pTriBin(0:10,10,.4)#acquiring the cumulative probability values