The function may be called by the names: g01ebc, nag_stat_prob_students_t or nag_prob_students_t.
The lower tail probability for the Student's -distribution with degrees of freedom, is defined by:
Computationally, there are two situations:
(i)when , a transformation of the beta distribution, is used
(ii)when , an asymptotic normalizing expansion of the Cornish–Fisher type is used to evaluate the probability, see Hill (1970).
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 -distribution Comm. ACM13(10) 617–619
1: – Nag_TailProbabilityInput
On entry: indicates which tail the returned probability should represent.
The upper tail probability is returned, i.e., .
The two tail (significance level) probability is returned, i.e., .
The two tail (confidence interval) probability is returned, i.e., .
The lower tail probability is returned, i.e., .
, , or .
2: – doubleInput
On entry: , the value of the Student's variate.
3: – doubleInput
On entry: , the degrees of freedom of the Student's -distribution.
4: – NagError *Input/Output
The NAG error argument (see Section 7 in the Introduction to the NAG Library CL Interface).
6Error Indicators and Warnings
If NE_NOERROR, then g01ebc returns .
Dynamic memory allocation failed.
See Section 3.1.2 in the Introduction to the NAG Library CL Interface for further information.
On entry, argument 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.
See Section 7.5 in the Introduction to the NAG Library CL 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 CL Interface for further information.
On entry, .
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 ), see Hastings and Peacock (1975).
8Parallelism and Performance
g01ebc is not threaded in any implementation.
The probabilities could also be obtained by using the appropriate transformation to a beta distribution (see Abramowitz and Stegun (1972)) and using g01eec. This function allows you to set the required accuracy.
This example reads values from, and degrees of freedom for Student's -distributions along with the required tail. The probabilities are calculated and printed until the end of data is reached.