These functions provide the ability for generating probability function values and cumulative probability function values for the Multiplicative Binomial Distribution.
pMultiBin(x,n,p,theta)
x | vector of binomial random variables. |
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n | single value for no of binomial trials. |
p | single value for probability of success. |
theta | single value for theta. |
The output of pMultiBin
gives cumulative probability values in vector form.
The probability function and cumulative function can be constructed and are denoted below
The cumulative probability function is the summation of probability function values.
$$P_{MultiBin}(x)= {n \choose x} p^x (1-p)^{n-x} \frac{(theta^{x(n-x)}}{f(p,theta,n)} $$
here \(f(p,theta,n)\) is $$f(p,theta,n)= \sum_{k=0}^{n} {n \choose k} p^k (1-p)^{n-k} (theta^{k(n-k)} )$$
$$x = 0,1,2,3,...n$$ $$n = 1,2,3,...$$ $$k = 0,1,2,...,n$$ $$0 < p < 1$$ $$0 < theta $$
NOTE : If input parameters are not in given domain conditions necessary error messages will be provided to go further.
Johnson, N. L., Kemp, A. W., & Kotz, S. (2005). Univariate discrete distributions (Vol. 444). Hoboken, NJ: Wiley-Interscience.
L. L. Kupper, J.K.H., 1978. The Use of a Correlated Binomial Model for the Analysis of Certain Toxicological Experiments. Biometrics, 34(1), pp.69-76.
Paul, S.R., 1985. A three-parameter generalization of the binomial distribution. Communications in Statistics - Theory and Methods, 14(6), pp.1497-1506.
Available at: http://www.tandfonline.com/doi/abs/10.1080/03610928508828990.
#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) }#> [1] 6.364309e-29 8.964365e-19 5.657070e-11 2.106255e-05 5.123785e-02 #> [6] 8.509524e-01 9.771209e-02 7.659947e-05 3.923411e-10 1.185630e-17 #> [11] 1.605234e-27#> [1] 5.046585#> [1] 0.1471704#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#> [1] 6.364309e-29 8.964365e-19 5.657070e-11 2.106261e-05 5.125891e-02 #> [6] 9.022113e-01 9.999234e-01 1.000000e+00 1.000000e+00 1.000000e+00 #> [11] 1.000000e+00