NAG CL Interface
g01hac (prob_bivariate_normal)

For a more detailed description of the bivariate Normal distribution and its properties see Abramowitz and Stegun (1972) and Kendall and Stuart (1969). The method used is described by Genz (2004).

4 References

Abramowitz M and Stegun I A (1972) Handbook of Mathematical Functions (3rd Edition) Dover Publications

Genz A (2004) Numerical computation of rectangular bivariate and trivariate Normal and

t

probabilities Statistics and Computing 14 151–160

Kendall M G and Stuart A (1969) The Advanced Theory of Statistics (Volume 1) (3rd Edition) Griffin

5 Arguments

1: $x$ – double Input: On entry: $x$ , the first argument for which the bivariate Normal distribution function is to be evaluated.
2: $y$ – double Input: On entry: $y$ , the second argument for which the bivariate Normal distribution function is to be evaluated.
3: $rho$ – double Input: On entry: $ρ$ , the correlation coefficient.

Constraint: $- 1.0 \leq rho \leq 1.0$ .
4: $fail$ – NagError * Input/Output: The NAG error argument (see Section 7 in the Introduction to the NAG Library CL Interface).

6 Error Indicators and Warnings

On any of the error conditions listed below g01hac returns $0.0$ .
NE_ALLOC_FAIL: Dynamic memory allocation failed.
See Section 3.1.2 in the Introduction to the NAG Library CL Interface for further information.
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.
See Section 7.5 in the Introduction to the NAG Library CL Interface for further information.
NE_NO_LICENCE: 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.
NE_REAL_ARG_GT: On entry, $rho = ⟨ value ⟩$ .
Constraint: $rho \leq 1.0$ .
NE_REAL_ARG_LT: On entry, $rho = ⟨ value ⟩$ .
Constraint: $rho \geq - 1.0$ .

7 Accuracy

Accuracy of the hybrid algorithm implemented here is discussed in Genz (2004). This algorithm should give a maximum absolute error of less than

5 \times 10^{−16}

8 Parallelism and Performance

Background information to multithreading can be found in the Multithreading documentation.

g01hac 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 X06 Chapter Introduction for information on how to control and interrogate the OpenMP environment used within this function. Please also consult the Users' Note for your implementation for any additional implementation-specific information.

9 Further Comments

The probabilities for the univariate Normal distribution can be computed using s15abc and s15acc.

10 Example

This example reads values of

x

and

y

for a bivariate Normal distribution along with the value of

ρ

and computes the lower tail probabilities.

NAG CL Interfaceg01hac (prob_​bivariate_​normal)

▸▿ Contents

1 Purpose

2 Specification

3 Description