These functions provide the ability for generating probability density values, cumulative probability density values and moment about zero values for the Generalized Beta Type-1 Distribution bounded between [0,1].
pGBeta1(p,a,b,c)
Arguments
p: vector of probabilities.
a: single value for shape parameter alpha representing as a.
b: single value for shape parameter beta representing as b.
c: single value for shape parameter gamma representing as c.
Returns
The output pGBeta1 gives the cumulative density values in vector form.
Details
The probability density function and cumulative density function of a unit bounded Generalized Beta Type-1 Distribution with random variable P are given by
Defined as B(a,b) is Beta function. Defined as 2F1(a,b;c;d) is Gaussian Hypergeometric 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(5)a <- c(.1,.2,.3,1.5,2.15)plot(0,0,main="Probability density graph",xlab="Random variable",ylab="Probability density values",xlim = c(0,1),ylim = c(0,10))for(i in1:5){lines(seq(0,1,by=0.001),dGBeta1(seq(0,1,by=0.001),a[i],1,2*a[i])$pdf,col = col[i])}dGBeta1(seq(0,1,by=0.01),2,3,1)$pdf #extracting the pdf valuesdGBeta1(seq(0,1,by=0.01),2,3,1)$mean #extracting the meandGBeta1(seq(0,1,by=0.01),2,3,1)$var #extracting the variancepGBeta1(0.04,2,3,4)#acquiring the cdf values for a=2,b=3,c=4mazGBeta1(1.4,3,2,2)#acquiring the moment about zero valuesmazGBeta1(2,3,2,2)-mazGBeta1(1,3,2,2)^2#acquiring the variance for a=3,b=2,c=2#only the integer value of moments is taken here because moments cannot be decimalmazGBeta1(3.2,3,2,2)