nag_prob_gamma_vector (g01sfc) (PDF version)
g01 Chapter Contents
g01 Chapter Introduction
NAG Library Manual

NAG Library Function Document

nag_prob_gamma_vector (g01sfc)

 Contents

    1  Purpose
    7  Accuracy

1  Purpose

nag_prob_gamma_vector (g01sfc) returns a number of lower or upper tail probabilities for the gamma distribution.

2  Specification

#include <nag.h>
#include <nagg01.h>
void  nag_prob_gamma_vector (Integer ltail, const Nag_TailProbability tail[], Integer lg, const double g[], Integer la, const double a[], Integer lb, const double b[], double p[], Integer ivalid[], NagError *fail)

3  Description

The lower tail probability for the gamma distribution with parameters αi and βi, PGigi, is defined by:
P Gi gi :αi,βi = 1 βi αi Γ αi 0 gi Gi αi-1 e -Gi/βi dGi ,   αi>0.0 , ​ βi>0.0 .  
The mean of the distribution is αiβi and its variance is αiβi2. The transformation Zi=Giβi is applied to yield the following incomplete gamma function in normalized form,
P Gi gi :αi,βi = P Zi gi / βi :αi,1.0 = 1 Γ αi 0 gi / βi Zi αi-1 e -Zi dZi .  
This is then evaluated using nag_incomplete_gamma (s14bac).
The input arrays to this function 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

Hastings N A J and Peacock J B (1975) Statistical Distributions Butterworth

5  Arguments

1:     ltail IntegerInput
On entry: the length of the array tail.
Constraint: ltail>0.
2:     tail[ltail] const Nag_TailProbabilityInput
On entry: indicates whether a lower or upper tail probability is required. For j= i-1 mod ltail , for i=1,2,,maxltail,lg,la,lb:
tail[j]=Nag_LowerTail
The lower tail probability is returned, i.e., pi = P Gi gi :αi,βi .
tail[j]=Nag_UpperTail
The upper tail probability is returned, i.e., pi = P Gi gi :αi,βi .
Constraint: tail[j-1]=Nag_LowerTail or Nag_UpperTail, for j=1,2,,ltail.
3:     lg IntegerInput
On entry: the length of the array g.
Constraint: lg>0.
4:     g[lg] const doubleInput
On entry: gi, the value of the gamma variate with gi=g[j], j=i-1 mod lg.
Constraint: g[j-1]0.0, for j=1,2,,lg.
5:     la IntegerInput
On entry: the length of the array a.
Constraint: la>0.
6:     a[la] const doubleInput
On entry: the parameter αi of the gamma distribution with αi=a[j], j=i-1 mod la.
Constraint: a[j-1]>0.0, for j=1,2,,la.
7:     lb IntegerInput
On entry: the length of the array b.
Constraint: lb>0.
8:     b[lb] const doubleInput
On entry: the parameter βi of the gamma distribution with βi=b[j], j=i-1 mod lb.
Constraint: b[j-1]>0.0, for j=1,2,,lb.
9:     p[dim] doubleOutput
Note: the dimension, dim, of the array p must be at least maxlg,la,lb,ltail.
On exit: pi, the probabilities of the beta distribution.
10:   ivalid[dim] IntegerOutput
Note: the dimension, dim, of the array ivalid must be at least maxlg,la,lb,ltail.
On exit: ivalid[i-1] indicates any errors with the input arguments, with
ivalid[i-1]=0
No error.
ivalid[i-1]=1
On entry,invalid value supplied in tail when calculating pi.
ivalid[i-1]=2
On entry,gi<0.0.
ivalid[i-1]=3
On entry,αi0.0,
orβi0.0.
ivalid[i-1]=4
The solution did not converge in 600 iterations, see nag_incomplete_gamma (s14bac) for details. The probability returned should be a reasonable approximation to the solution.
11:   fail NagError *Input/Output
The NAG error argument (see Section 2.7 in How to Use the NAG Library and its Documentation).

6  Error Indicators and Warnings

NE_ALLOC_FAIL
Dynamic memory allocation failed.
See Section 2.3.1.2 in How to Use the NAG Library and its Documentation for further information.
NE_ARRAY_SIZE
On entry, array size=value.
Constraint: la>0.
On entry, array size=value.
Constraint: lb>0.
On entry, array size=value.
Constraint: lg>0.
On entry, array size=value.
Constraint: ltail>0.
NE_BAD_PARAM
On entry, argument value had an illegal value.
NE_INTERNAL_ERROR
An internal error has occurred in this function. Check the function call and any array sizes. If the call is correct then please contact NAG for assistance.
An unexpected error has been triggered by this function. Please contact NAG.
See Section 2.7.6 in How to Use the NAG Library and its Documentation for further information.
NE_NO_LICENCE
Your licence key may have expired or may not have been installed correctly.
See Section 2.7.5 in How to Use the NAG Library and its Documentation for further information.
NW_IVALID
On entry, at least one value of g, a, b or tail was invalid, or the solution did not converge.
Check ivalid for more information.

7  Accuracy

The result should have a relative accuracy of machine precision. There are rare occasions when the relative accuracy attained is somewhat less than machine precision but the error should not exceed more than 1 or 2 decimal places.

8  Parallelism and Performance

nag_prob_gamma_vector (g01sfc) is not threaded in any implementation.

9  Further Comments

The time taken by nag_prob_gamma_vector (g01sfc) to calculate each probability varies slightly with the input arguments gi, αi and βi.

10  Example

This example reads in values from a number of gamma distributions and computes the associated lower tail probabilities.

10.1  Program Text

Program Text (g01sfce.c)

10.2  Program Data

Program Data (g01sfce.d)

10.3  Program Results

Program Results (g01sfce.r)


nag_prob_gamma_vector (g01sfc) (PDF version)
g01 Chapter Contents
g01 Chapter Introduction
NAG Library Manual

© The Numerical Algorithms Group Ltd, Oxford, UK. 2016