S17ARF (PDF version)
S Chapter Contents
S Chapter Introduction
NAG Library Manual

NAG Library Routine Document


Note:  before using this routine, please read the Users' Note for your implementation to check the interpretation of bold italicised terms and other implementation-dependent details.

+ Contents

    1  Purpose
    7  Accuracy

1  Purpose

S17ARF returns an array of values of the Bessel function Y1x.

2  Specification

REAL (KIND=nag_wp)  X(N), F(N)

3  Description

S17ARF evaluates an approximation to the Bessel function of the second kind Y1xi for an array of arguments xi, for i=1,2,,n.
Note:  Y1x is undefined for x0 and the routine will fail for such arguments.
The routine is based on four Chebyshev expansions:
For 0<x8,
Y1 x = 2π lnx x8 r=0 ar Tr t - 2πx + x8 r=0 br Tr t ,   with ​ t = 2 x8 2 - 1 .
For x>8,
Y1 x = 2πx P1 x sin x - 3 π4 + Q1 x cos x - 3 π4
where P1 x = r=0 cr Tr t ,
and Q1 x = 8x r=0 dr Tr t , with t = 2 8x 2 - 1 .
For x near zero, Y1 x - 2 πx . This approximation is used when x is sufficiently small for the result to be correct to machine precision. For extremely small x, there is a danger of overflow in calculating - 2 πx  and for such arguments the routine will fail.
For very large x, it becomes impossible to provide results with any reasonable accuracy (see Section 7), hence the routine fails. Such arguments contain insufficient information to determine the phase of oscillation of Y1x; only the amplitude, 2πx , can be determined and this is returned on soft failure. The range for which this occurs is roughly related to machine precision; the routine will fail if x1/machine precision (see the Users' Note for your implementation for details).

4  References

Abramowitz M and Stegun I A (1972) Handbook of Mathematical Functions (3rd Edition) Dover Publications
Clenshaw C W (1962) Chebyshev Series for Mathematical Functions Mathematical tables HMSO

5  Parameters

1:     N – INTEGERInput
On entry: n, the number of points.
Constraint: N0.
2:     X(N) – REAL (KIND=nag_wp) arrayInput
On entry: the argument xi of the function, for i=1,2,,N.
Constraint: Xi>0.0, for i=1,2,,N.
3:     F(N) – REAL (KIND=nag_wp) arrayOutput
On exit: Y1xi, the function values.
4:     IVALID(N) – INTEGER arrayOutput
On exit: IVALIDi contains the error code for xi, for i=1,2,,N.
No error.
On entry,xi is too large. Fi contains the amplitude of the Y1 oscillation, 2πxi .
On entry,xi0.0, Y1 is undefined. Fi contains 0.0.
xi is too close to zero, there is a danger of overflow. On soft failure, Fi contains the value of Y1x at the smallest valid argument.
5:     IFAIL – INTEGERInput/Output
On entry: IFAIL must be set to 0, -1​ or ​1. If you are unfamiliar with this parameter you should refer to Section 3.3 in the Essential Introduction for details.
For environments where it might be inappropriate to halt program execution when an error is detected, the value -1​ or ​1 is recommended. If the output of error messages is undesirable, then the value 1 is recommended. Otherwise, if you are not familiar with this parameter, the recommended value is 0. When the value -1​ or ​1 is used it is essential to test the value of IFAIL on exit.
On exit: IFAIL=0 unless the routine detects an error or a warning has been flagged (see Section 6).

6  Error Indicators and Warnings

If on entry IFAIL=0 or -1, explanatory error messages are output on the current error message unit (as defined by X04AAF).
Errors or warnings detected by the routine:
On entry, at least one value of X was invalid.
Check IVALID for more information.
On entry, N=value.
Constraint: N0.

7  Accuracy

Let δ be the relative error in the argument and E be the absolute error in the result. (Since Y1x oscillates about zero, absolute error and not relative error is significant, except for very small x.)
If δ is somewhat larger than the machine precision (e.g., if δ is due to data errors etc.), then E and δ are approximately related by:
E x Y0 x - Y1 x δ
(provided E is also within machine bounds). Figure 1 displays the behaviour of the amplification factor xY0x-Y1x.
However, if δ is of the same order as machine precision, then rounding errors could make E slightly larger than the above relation predicts.
For very small x, absolute error becomes large, but the relative error in the result is of the same order as δ.
For very large x, the above relation ceases to apply. In this region, Y1 x 2 πx sin x - 3π 4 . The amplitude 2 πx  can be calculated with reasonable accuracy for all x, but sinx- 3π4  cannot. If x- 3π4  is written as 2Nπ+θ where N is an integer and 0θ<2π, then sinx- 3π4 is determined by θ only. If x>δ-1, θ cannot be determined with any accuracy at all. Thus if x is greater than, or of the order of, the inverse of the machine precision, it is impossible to calculate the phase of Y1x and the routine must fail.
Figure 1
Figure 1

8  Further Comments


9  Example

This example reads values of X from a file, evaluates the function at each value of xi and prints the results.

9.1  Program Text

Program Text (s17arfe.f90)

9.2  Program Data

Program Data (s17arfe.d)

9.3  Program Results

Program Results (s17arfe.r)

S17ARF (PDF version)
S Chapter Contents
S Chapter Introduction
NAG Library Manual

© The Numerical Algorithms Group Ltd, Oxford, UK. 2012