NAG Library Function Document
nag_multi_students_t (g01hdc)
1 Purpose
nag_multi_students_t (g01hdc) returns a probability associated with a multivariate Student's -distribution.
2 Specification
#include <nag.h> |
#include <nagg01.h> |
double |
nag_multi_students_t (Integer n,
const Nag_TailProbability tail[],
const double a[],
const double b[],
double nu,
const double delta[],
Nag_Boolean iscov,
double rc[],
Integer pdrc,
double epsabs,
double epsrel,
Integer numsub,
Integer nsampl,
Integer fmax,
double *errest,
NagError *fail) |
|
3 Description
A random vector
that follows a Student's
-distribution with
degrees of freedom and covariance matrix
has density:
and probability
given by:
The method of calculation depends on the dimension and degrees of freedom . The method of Dunnet and Sobel is used in the bivariate case if is a whole number. A Plackett transform followed by quadrature method is adopted in other bivariate cases and trivariate cases. In dimensions higher than three a number theoretic approach to evaluating multidimensional integrals is adopted.
Error estimates are supplied as the published accuracy in the Dunnet and Sobel case, a Monte–Carlo standard error for multidimensional integrals, and otherwise the quadrature error estimate.
A parameter allows for non-central probabilities. The number theoretic method is used if any is nonzero.
In cases other than the central bivariate with whole , nag_multi_students_t (g01hdc) attempts to evaluate probabilities within a requested accuracy , for an approximate integral value , absolute accuracy and relative accuracy .
4 References
Dunnet C W and Sobel M (1954) A bivariate generalization of Student's -distribution, with tables for certain special cases Biometrika 41 153–169
Genz A and Bretz F (2002) Methods for the computation of multivariate -probabilities Journal of Computational and Graphical Statistics (11) 950–971
5 Arguments
- 1:
n – IntegerInput
On entry: , the number of dimensions.
Constraint:
.
- 2:
tail[n] – const Nag_TailProbabilityInput
On entry: defines the calculated probability, set
to:
- If the th lower limit is negative infinity.
- If the th upper limit is infinity.
- If both and are finite.
Constraint:
, or , for .
- 3:
a[n] – const doubleInput
On entry:
, for
, the lower integral limits of the calculation.
If , is not referenced and the th lower limit of integration is .
- 4:
b[n] – const doubleInput
On entry:
, for
, the upper integral limits of the calculation.
If , is not referenced and the th upper limit of integration is .
Constraint:
if , .
- 5:
nu – doubleInput
On entry: , the degrees of freedom.
Constraint:
.
- 6:
delta[n] – const doubleInput
On entry: the noncentrality parameter for the th dimension, for ; set for the central probability.
- 7:
iscov – Nag_BooleanInput
On entry: set if the covariance matrix is supplied and if the correlation matrix is supplied.
- 8:
rc[] – doubleInput/Output
-
Note: the th element of the matrix is stored in .
On entry: the lower triangle of either the covariance matrix (if ) or the correlation matrix (if ). In either case the array elements corresponding to the upper triangle of the matrix need not be set.
On exit: the strict upper triangle of
rc contains the correlation matrix used in the calculations.
- 9:
pdrc – IntegerInput
-
On entry: the stride separating matrix column elements in the array
rc.
Constraint:
.
- 10:
epsabs – doubleInput
On entry:
, the absolute accuracy requested in the approximation. If
epsabs is negative, the absolute value is used.
Suggested value:
.
- 11:
epsrel – doubleInput
On entry:
, the relative accuracy requested in the approximation. If
epsrel is negative, the absolute value is used.
Suggested value:
.
- 12:
numsub – IntegerInput
-
On entry: if quadrature is used, the number of sub-intervals used by the quadrature algorithm; otherwise
numsub is not referenced.
Suggested value:
.
Constraint:
if referenced, .
- 13:
nsampl – IntegerInput
On entry: if quadrature is used,
nsampl is not referenced; otherwise
nsampl is the number of samples used to estimate the error in the approximation.
Suggested value:
Constraint:
if referenced, .
- 14:
fmax – IntegerInput
On entry: if a number theoretic approach is used, the maximum number of evaluations for each integrand function.
Suggested value:
Constraint:
if referenced, .
- 15:
errest – double *Output
On exit: an estimate of the error in the calculated probability.
- 16:
fail – NagError *Input/Output
-
The NAG error argument (see
Section 3.6 in the Essential Introduction).
6 Error Indicators and Warnings
- NE_ALLOC_FAIL
-
Dynamic memory allocation failed.
- NE_ARRAY_SIZE
-
On entry, and .
Constraint: .
- NE_BAD_PARAM
-
On entry, argument had an illegal value.
- NE_INT
-
On entry, .
Constraint: .
On entry, .
Constraint: .
On entry, .
Constraint: .
On entry, .
Constraint: .
- 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.
- NE_INVALID_ARRAY
-
On entry, the information supplied in
rc is invalid.
- NE_REAL
-
On entry, .
Constraint: degrees of freedom .
- NE_REAL_2
-
On entry, .
Constraint: for a central probability.
7 Accuracy
An estimate of the error in the calculation is given by the value of
errest on exit.
8 Parallelism and Performance
nag_multi_students_t (g01hdc) is not threaded by NAG in any implementation.
nag_multi_students_t (g01hdc) makes calls to BLAS and/or LAPACK routines, which may be threaded within the vendor library used by this implementation. Consult the documentation for the vendor library for further information.
Please consult the
Users' Note for your implementation for any additional implementation-specific information.
None.
10 Example
This example prints two probabilities from the Student's -distribution.
10.1 Program Text
Program Text (g01hdce.c)
10.2 Program Data
Program Data (g01hdce.d)
10.3 Program Results
Program Results (g01hdce.r)