NAG FL Interface
g05sbf (dist_​beta)

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1 Purpose

g05sbf generates a vector of pseudorandom numbers taken from a beta distribution with parameters a and b.

2 Specification

Fortran Interface
Subroutine g05sbf ( n, a, b, state, x, ifail)
Integer, Intent (In) :: n
Integer, Intent (Inout) :: state(*), ifail
Real (Kind=nag_wp), Intent (In) :: a, b
Real (Kind=nag_wp), Intent (Out) :: x(n)
C Header Interface
#include <nag.h>
void  g05sbf_ (const Integer *n, const double *a, const double *b, Integer state[], double x[], Integer *ifail)
The routine may be called by the names g05sbf or nagf_rand_dist_beta.

3 Description

The beta distribution has PDF (probability density function)
f(x) = Γ(a+b) Γ(a) Γ(b) xa-1 (1-x) b-1 if  0x1 ; ​ a,b>0 , f(x)=0 otherwise.  
One of four algorithms is used to generate the variates depending on the values of a and b. Let α be the maximum and β be the minimum of a and b. Then the algorithms are as follows:
  1. (i)if α<0.5, Johnk's algorithm is used, see for example Dagpunar (1988). This generates the beta variate as u11/a/ ( u11/a+u21/b ) , where u1 and u2 are uniformly distributed random variates;
  2. (ii)if β>1, the algorithm BB given by Cheng (1978) is used. This involves the generation of an observation from a beta distribution of the second kind by the envelope rejection method using a log-logistic target distribution and then transforming it to a beta variate;
  3. (iii)if α>1 and β<1, the switching algorithm given by Atkinson (1979) is used. The two target distributions used are f1(x)=βxβ and f2(x)=α(1-x)β-1, along with the approximation to the switching parameter of t=(1-β)/(α+1-β);
  4. (iv)in all other cases, Cheng's BC algorithm (see Cheng (1978)) is used with modifications suggested by Dagpunar (1988). This algorithm is similar to BB, used when β>1, but is tuned for small values of a and b.
One of the initialization routines g05kff (for a repeatable sequence if computed sequentially) or g05kgf (for a non-repeatable sequence) must be called prior to the first call to g05sbf.

4 References

Atkinson A C (1979) A family of switching algorithms for the computer generation of beta random variates Biometrika 66 141–5
Cheng R C H (1978) Generating beta variates with nonintegral shape parameters Comm. ACM 21 317–322
Dagpunar J (1988) Principles of Random Variate Generation Oxford University Press
Hastings N A J and Peacock J B (1975) Statistical Distributions Butterworth

5 Arguments

1: n Integer Input
On entry: n, the number of pseudorandom numbers to be generated.
Constraint: n0.
2: a Real (Kind=nag_wp) Input
On entry: a, the parameter of the beta distribution.
Constraint: a>0.0.
3: b Real (Kind=nag_wp) Input
On entry: b, the parameter of the beta distribution.
Constraint: b>0.0.
4: state(*) Integer array Communication Array
Note: the actual argument supplied must be the array state supplied to the initialization routines g05kff or g05kgf.
On entry: contains information on the selected base generator and its current state.
On exit: contains updated information on the state of the generator.
5: x(n) Real (Kind=nag_wp) array Output
On exit: the n pseudorandom numbers from the specified beta distribution.
6: ifail Integer Input/Output
On entry: ifail must be set to 0, −1 or 1 to set behaviour on detection of an error; these values have no effect when no error is detected.
A value of 0 causes the printing of an error message and program execution will be halted; otherwise program execution continues. A value of −1 means that an error message is printed while a value of 1 means that it is not.
If halting is not appropriate, the value −1 or 1 is recommended. If message printing is undesirable, then the value 1 is recommended. Otherwise, the value 0 is recommended. When the value -1 or 1 is used it is essential to test the value of ifail on exit.
On exit: ifail=0 unless the routine detects an error or a warning has been flagged (see Section 6).

6 Error Indicators and Warnings

If on entry ifail=0 or −1, explanatory error messages are output on the current error message unit (as defined by x04aaf).
Errors or warnings detected by the routine:
ifail=1
On entry, n=value.
Constraint: n0.
ifail=2
On entry, a=value.
Constraint: a>0.0.
ifail=3
On entry, b=value.
Constraint: b>0.0.
ifail=4
On entry, state vector has been corrupted or not initialized.
ifail=-99
An unexpected error has been triggered by this routine. Please contact NAG.
See Section 7 in the Introduction to the NAG Library FL Interface for further information.
ifail=-399
Your licence key may have expired or may not have been installed correctly.
See Section 8 in the Introduction to the NAG Library FL Interface for further information.
ifail=-999
Dynamic memory allocation failed.
See Section 9 in the Introduction to the NAG Library FL Interface for further information.

7 Accuracy

Not applicable.

8 Parallelism and Performance

Background information to multithreading can be found in the Multithreading documentation.
g05sbf is threaded by NAG for parallel execution in multithreaded implementations of the NAG Library.
Please consult the X06 Chapter Introduction for information on how to control and interrogate the OpenMP environment used within this routine. Please also consult the Users' Note for your implementation for any additional implementation-specific information.

9 Further Comments

To generate an observation, y, from the beta distribution of the second kind from an observation, x, generated by g05sbf the transformation, y=x/(1-x), may be used.

10 Example

This example prints a set of five pseudorandom numbers from a beta distribution with parameters a=2.0 and b=2.0, generated by a single call to g05sbf, after initialization by g05kff.

10.1 Program Text

Program Text (g05sbfe.f90)

10.2 Program Data

Program Data (g05sbfe.d)

10.3 Program Results

Program Results (g05sbfe.r)