dMultiBin function

Multiplicative Binomial Distribution

Multiplicative Binomial Distribution

These functions provide the ability for generating probability function values and cumulative probability function values for the Multiplicative Binomial Distribution.

dMultiBin(x,n,p,theta)

Arguments

  • x: vector of binomial random variables.
  • n: single value for no of binomial trials.
  • p: single value for probability of success.
  • theta: single value for theta.

Returns

The output of dMultiBin gives a list format consisting

pdf probability function values in vector form.

mean mean of Multiplicative Binomial Distribution.

var variance of Multiplicative 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.

PMultiBin(x)=(nx)px(1p)nx(thetax(nx)f(p,theta,n) P_{MultiBin}(x)= {n \choose x} p^x (1-p)^{n-x} \frac{(theta^{x(n-x)}}{f(p,theta,n)}

here f(p,theta,n)f(p,theta,n) is

f(p,theta,n)=k=0n(nk)pk(1p)nk(thetak(nk)) f(p,theta,n)= \sum_{k=0}^{n} {n \choose k} p^k (1-p)^{n-k} (theta^{k(n-k)} ) x=0,1,2,3,...n x = 0,1,2,3,...n n=1,2,3,... n = 1,2,3,... k=0,1,2,...,n k = 0,1,2,...,n 0<p<1 0 < p < 1 0<theta 0 < theta

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 values col <- 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="Multiplicative binomial probability function graph",xlab="Binomial random variable", ylab="Probability function values",xlim = c(0,10),ylim = c(0,0.5)) for (i in 1:5) { lines(0:10,dMultiBin(0:10,10,a[i],1+b[i])$pdf,col = col[i],lwd=2.85) points(0:10,dMultiBin(0:10,10,a[i],1+b[i])$pdf,col = col[i],pch=16) } dMultiBin(0:10,10,.58,10.022)$pdf #extracting the pdf values dMultiBin(0:10,10,.58,10.022)$mean #extracting the mean dMultiBin(0:10,10,.58,10.022)$var #extracting the variance #plotting random variables and cumulative probability values col <- 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="Multiplicative binomial probability function graph",xlab="Binomial random variable", ylab="Probability function values",xlim = c(0,10),ylim = c(0,1)) for (i in 1:5) { lines(0:10,pMultiBin(0:10,10,a[i],1+b[i]),col = col[i],lwd=2.85) points(0:10,pMultiBin(0:10,10,a[i],1+b[i]),col = col[i],pch=16) } pMultiBin(0:10,10,.58,10.022) #acquiring the cumulative probability values

References

\insertRef johnson2005univariatefitODBOD

\insertRef kupper1978usefitODBOD

\insertRef paul1985threefitODBOD