These functions provide the ability for generating probability function values and cumulative probability function values for the Additive Binomial Distribution.
dAddBin(x,n,p,alpha)
Arguments
x: vector of binomial random variables.
n: single value for no of binomial trials.
p: single value for probability of success
alpha: single value for alpha parameter.
Returns
The output of dAddBin gives a list format consisting
pdf probability function values in vector form.
mean mean of Additive Binomial Distribution.
var variance of Additive Binomial Distribution.
Details
The probability function and cumulative function can be constructed and are denoted below
The cumulative probability function is the summation of probability function values.
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(5)a <- c(0.58,0.59,0.6,0.61,0.62)b <- c(0.022,0.023,0.024,0.025,0.026)plot(0,0,main="Additive binomial probability function graph",xlab="Binomial random variable",ylab="Probability function values",xlim = c(0,10),ylim = c(0,0.5))for(i in1:5){ lines(0:10,dAddBin(0:10,10,a[i],b[i])$pdf,col = col[i],lwd=2.85) points(0:10,dAddBin(0:10,10,a[i],b[i])$pdf,col = col[i],pch=16)}dAddBin(0:10,10,0.58,0.022)$pdf #extracting the probability valuesdAddBin(0:10,10,0.58,0.022)$mean #extracting the meandAddBin(0:10,10,0.58,0.022)$var #extracting the variance#plotting the random variables and cumulative probability valuescol <- rainbow(5)a <- c(0.58,0.59,0.6,0.61,0.62)b <- c(0.022,0.023,0.024,0.025,0.026)plot(0,0,main="Additive binomial probability function graph",xlab="Binomial random variable",ylab="Probability function values",xlim = c(0,10),ylim = c(0,1))for(i in1:5){lines(0:10,pAddBin(0:10,10,a[i],b[i]),col = col[i],lwd=2.85)points(0:10,pAddBin(0:10,10,a[i],b[i]),col = col[i],pch=16)}pAddBin(0:10,10,0.58,0.022)#acquiring the cumulative probability values