NAG FL Interface
g01tff (inv_​cdf_​gamma_​vector)

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1 Purpose

g01tff returns a number of deviates associated with given probabilities of the gamma distribution.

2 Specification

Fortran Interface
Subroutine g01tff ( ltail, tail, lp, p, la, a, lb, b, tol, g, ivalid, ifail)
Integer, Intent (In) :: ltail, lp, la, lb
Integer, Intent (Inout) :: ifail
Integer, Intent (Out) :: ivalid(*)
Real (Kind=nag_wp), Intent (In) :: p(lp), a(la), b(lb), tol
Real (Kind=nag_wp), Intent (Out) :: g(*)
Character (1), Intent (In) :: tail(ltail)
C Header Interface
#include <nag.h>
void  g01tff_ (const Integer *ltail, const char tail[], const Integer *lp, const double p[], const Integer *la, const double a[], const Integer *lb, const double b[], const double *tol, double g[], Integer ivalid[], Integer *ifail, const Charlen length_tail)
The routine may be called by the names g01tff or nagf_stat_inv_cdf_gamma_vector.

3 Description

The deviate, gpi, associated with the lower tail probability, pi, of the gamma distribution with shape parameter αi and scale parameter βi, is defined as the solution to
P( Gi gpi :αi,βi) = pi = 1 βi αi Γ (αi) 0 gpi ei - Gi / βi Gi αi-1 dGi ,   0 gpi < ; ​ αi , βi > 0 .  
The method used is described by Best and Roberts (1975) making use of the relationship between the gamma distribution and the χ2-distribution.
Let yi=2 gpiβi . The required yi is found from the Taylor series expansion
yi=y0+rCr(y0) r! (Eiϕ(y0) ) r,  
where y0 is a starting approximation
For most values of pi and αi the starting value
y01=2αi (zi19αi +1-19αi ) 3  
is used, where zi is the deviate associated with a lower tail probability of pi for the standard Normal distribution.
For pi close to zero,
y02= (piαi2αiΓ(αi)) 1/αi  
is used.
For large pi values, when y01>4.4αi+6.0,
is found to be a better starting value than y01.
For small αi (αi0.16), pi is expressed in terms of an approximation to the exponential integral and y04 is found by Newton–Raphson iterations.
Seven terms of the Taylor series are used to refine the starting approximation, repeating the process if necessary until the required accuracy is obtained.
The input arrays to this routine are designed to allow maximum flexibility in the supply of vector arguments by re-using elements of any arrays that are shorter than the total number of evaluations required. See Section 2.6 in the G01 Chapter Introduction for further information.

4 References

Best D J and Roberts D E (1975) Algorithm AS 91. The percentage points of the χ2 distribution Appl. Statist. 24 385–388

5 Arguments

1: ltail Integer Input
On entry: the length of the array tail.
Constraint: ltail>0.
2: tail(ltail) Character(1) array Input
On entry: indicates which tail the supplied probabilities represent. For j= ((i-1) mod ltail) +1 , for i=1,2,,max(ltail,lp,la,lb):
The lower tail probability, i.e., pi = P( Gi gpi : αi , βi ) .
The upper tail probability, i.e., pi = P( Gi gpi : αi , βi ) .
Constraint: tail(j)='L' or 'U', for j=1,2,,ltail.
3: lp Integer Input
On entry: the length of the array p.
Constraint: lp>0.
4: p(lp) Real (Kind=nag_wp) array Input
On entry: pi, the probability of the required gamma distribution as defined by tail with pi=p(j), j=((i-1) mod lp)+1.
  • if tail(k)='L', 0.0p(j)<1.0;
  • otherwise 0.0<p(j)1.0.
Where k=(i-1) mod ltail+1 and j=(i-1) mod lp+1.
5: la Integer Input
On entry: the length of the array a.
Constraint: la>0.
6: a(la) Real (Kind=nag_wp) array Input
On entry: αi, the first parameter of the required gamma distribution with αi=a(j), j=((i-1) mod la)+1.
Constraint: 0.0<a(j)106, for j=1,2,,la.
7: lb Integer Input
On entry: the length of the array b.
Constraint: lb>0.
8: b(lb) Real (Kind=nag_wp) array Input
On entry: βi, the second parameter of the required gamma distribution with βi=b(j), j=((i-1) mod lb)+1.
Constraint: b(j)>0.0, for j=1,2,,lb.
9: tol Real (Kind=nag_wp) Input
On entry: the relative accuracy required by you in the results. If g01tff is entered with tol greater than or equal to 1.0 or less than 10×machine precision (see x02ajf), the value of 10×machine precision is used instead.
10: g(*) Real (Kind=nag_wp) array Output
Note: the dimension of the array g must be at least max(ltail,lp,la,lb).
On exit: gpi, the deviates for the gamma distribution.
11: ivalid(*) Integer array Output
Note: the dimension of the array ivalid must be at least max(ltail,lp,la,lb).
On exit: ivalid(i) indicates any errors with the input arguments, with
No error.
On entry, invalid value supplied in tail when calculating gpi.
On entry, invalid value for pi.
On entry, αi0.0, or, αi>106, or, βi0.0.
pi is too close to 0.0 or 1.0 to enable the result to be calculated.
The solution has failed to converge. The result may be a reasonable approximation.
12: 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 −1 is recommended since useful values can be provided in some output arguments even when ifail0 on exit. 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:
Note: in some cases g01tff may return useful information.
On entry, at least one value of tail, p, a, or b was invalid.
Check ivalid for more information.
On entry, array size=value.
Constraint: ltail>0.
On entry, array size=value.
Constraint: lp>0.
On entry, array size=value.
Constraint: la>0.
On entry, array size=value.
Constraint: lb>0.
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.
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.
Dynamic memory allocation failed.
See Section 9 in the Introduction to the NAG Library FL Interface for further information.

7 Accuracy

In most cases the relative accuracy of the results should be as specified by tol. However, for very small values of αi or very small values of pi there may be some loss of accuracy.

8 Parallelism and Performance

Background information to multithreading can be found in the Multithreading documentation.
g01tff is not threaded in any implementation.

9 Further Comments


10 Example

This example reads lower tail probabilities for several gamma distributions, and calculates and prints the corresponding deviates until the end of data is reached.

10.1 Program Text

Program Text (g01tffe.f90)

10.2 Program Data

Program Data (g01tffe.d)

10.3 Program Results

Program Results (g01tffe.r)