nag_prob_students_t (g01ebc) (PDF version)
g01 Chapter Contents
g01 Chapter Introduction
NAG Library Manual

NAG Library Function Document

nag_prob_students_t (g01ebc)

+ Contents

    1  Purpose
    7  Accuracy

1  Purpose

nag_prob_students_t (g01ebc) returns the lower tail, upper tail or two tail probability for the Student's t-distribution with real degrees of freedom.

2  Specification

#include <nag.h>
#include <nagg01.h>
double  nag_prob_students_t (Nag_TailProbability tail, double t, double df, NagError *fail)

3  Description

The lower tail probability for the Student's t-distribution with ν degrees of freedom, PTt:ν is defined by:
P Tt:ν = Γ ν+1 / 2 πν Γν/2 - t 1+ T2ν -ν+1 / 2 dT ,   ν1 .
Computationally, there are two situations:
(i) when ν<20, a transformation of the beta distribution, PβBβ:a,b is used
P Tt:ν = 12 Pβ B ν ν+t2 : ν/2, 12   when ​ t<0.0
P Tt:ν = 12 + 12 Pβ B ν ν+t2 : ν/2, 12   when ​ t>0.0 ;
(ii) when ν20, an asymptotic normalizing expansion of the Cornish–Fisher type is used to evaluate the probability, see Hill (1970).

4  References

Abramowitz M and Stegun I A (1972) Handbook of Mathematical Functions (3rd Edition) Dover Publications
Hastings N A J and Peacock J B (1975) Statistical Distributions Butterworth
Hill G W (1970) Student's t-distribution Comm. ACM 13(10) 617–619

5  Arguments

1:     tailNag_TailProbabilityInput
On entry: indicates which tail the returned probability should represent.
The upper tail probability is returned, i.e., PTt:ν.
The two tail (significance level) probability is returned, i.e., PTt:ν+PT-t:ν.
The two tail (confidence interval) probability is returned, i.e., PTt:ν-PT-t:ν.
The lower tail probability is returned, i.e., PTt:ν.
Constraint: tail=Nag_UpperTail, Nag_TwoTailSignif, Nag_TwoTailConfid or Nag_LowerTail.
2:     tdoubleInput
On entry: t, the value of the Student's t variate.
3:     dfdoubleInput
On entry: ν, the degrees of freedom of the Student's t-distribution.
Constraint: df1.0.
4:     failNagError *Input/Output
The NAG error argument (see Section 3.6 in the Essential Introduction).

6  Error Indicators and Warnings

Dynamic memory allocation failed.
On entry, argument value had an illegal value.
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.
On entry, df=value.
Constraint: df1.0.

7  Accuracy

The computed probability should be accurate to five significant places for reasonable probabilities but there will be some loss of accuracy for very low probabilities (less than 10-10), see Hastings and Peacock (1975).

8  Parallelism and Performance

Not applicable.

9  Further Comments

The probabilities could also be obtained by using the appropriate transformation to a beta distribution (see Abramowitz and Stegun (1972)) and using nag_prob_beta_dist (g01eec). This function allows you to set the required accuracy.

10  Example

This example reads values from, and degrees of freedom for Student's t-distributions along with the required tail. The probabilities are calculated and printed until the end of data is reached.

10.1  Program Text

Program Text (g01ebce.c)

10.2  Program Data

Program Data (g01ebce.d)

10.3  Program Results

Program Results (g01ebce.r)

nag_prob_students_t (g01ebc) (PDF version)
g01 Chapter Contents
g01 Chapter Introduction
NAG Library Manual

© The Numerical Algorithms Group Ltd, Oxford, UK. 2014