nag_bessel_y1_vector (s17arc) (PDF version)
s Chapter Contents
s Chapter Introduction
NAG Library Manual

NAG Library Function Document

nag_bessel_y1_vector (s17arc)

 Contents

    1  Purpose
    7  Accuracy

1  Purpose

nag_bessel_y1_vector (s17arc) returns an array of values of the Bessel function Y1x.

2  Specification

#include <nag.h>
#include <nags.h>
void  nag_bessel_y1_vector (Integer n, const double x[], double f[], Integer ivalid[], NagError *fail)

3  Description

nag_bessel_y1_vector (s17arc) 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 function will fail for such arguments.
The function 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 function will fail.
For very large x, it becomes impossible to provide results with any reasonable accuracy (see Section 7), hence the function 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 failure. The range for which this occurs is roughly related to machine precision; the function 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  Arguments

1:     n IntegerInput
On entry: n, the number of points.
Constraint: n0.
2:     x[n] const doubleInput
On entry: the argument xi of the function, for i=1,2,,n.
Constraint: x[i-1]>0.0, for i=1,2,,n.
3:     f[n] doubleOutput
On exit: Y1xi, the function values.
4:     ivalid[n] IntegerOutput
On exit: ivalid[i-1] contains the error code for xi, for i=1,2,,n.
ivalid[i-1]=0
No error.
ivalid[i-1]=1
On entry,xi is too large. f[i-1] contains the amplitude of the Y1 oscillation, 2πxi .
ivalid[i-1]=2
On entry,xi0.0, Y1 is undefined. f[i-1] contains 0.0.
ivalid[i-1]=3
xi is too close to zero, there is a danger of overflow. On failure, f[i-1] contains the value of Y1x at the smallest valid argument.
5:     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.
See Section 3.2.1.2 in the Essential Introduction for further information.
NE_BAD_PARAM
On entry, argument value had an illegal value.
NE_INT
On entry, n=value.
Constraint: n0.
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.
An unexpected error has been triggered by this function. Please contact NAG.
See Section 3.6.6 in the Essential Introduction for further information.
NE_NO_LICENCE
Your licence key may have expired or may not have been installed correctly.
See Section 3.6.5 in the Essential Introduction for further information.
NW_IVALID
On entry, at least one value of x was invalid.
Check ivalid for more information.

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 function must fail.
Figure 1
Figure 1

8  Parallelism and Performance

Not applicable.

9  Further Comments

None.

10  Example

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

10.1  Program Text

Program Text (s17arce.c)

10.2  Program Data

Program Data (s17arce.d)

10.3  Program Results

Program Results (s17arce.r)


nag_bessel_y1_vector (s17arc) (PDF version)
s Chapter Contents
s Chapter Introduction
NAG Library Manual

© The Numerical Algorithms Group Ltd, Oxford, UK. 2015