For large negative arguments, it becomes impossible to calculate a result for the oscillating function with any accuracy and so the function must fail. This occurs for

x < - {(\frac{\sqrt{π}}{ε})}^{4 / 7}

, where

ε

is the machine precision.

For large positive arguments, where

{Ai}^{'}

decays in an essentially exponential manner, there is a danger of underflow so the function must fail.

4 References

NIST Digital Library of Mathematical Functions

5 Arguments

1: $x$ – double Input: On entry: the argument $x$ of the function.
2: $fail$ – NagError * Input/Output: The NAG error argument (see Section 7 in the Introduction to the NAG Library CL Interface).

6 Error Indicators and Warnings

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, $x = ⟨ value ⟩$ .
Constraint: $x \leq ⟨ value ⟩$ .
x is too large and positive. The function returns zero.
NE_REAL_ARG_LT: On entry, $x = ⟨ value ⟩$ .
Constraint: $x \geq ⟨ value ⟩$ .
x is too large and negative. The function returns zero.

7 Accuracy

For negative arguments the function is oscillatory and hence absolute error is the appropriate measure. In the positive region the function is essentially exponential in character and here relative error is needed. The absolute error,

E

, and the relative error,

ε

, are related in principle to the relative error in the argument,

δ

, by

E ≃ | x^{2} Ai (x) | δ ε ≃ | \frac{x^{2} Ai (x)}{{Ai}^{'} (x)} | δ .

In practice, approximate equality is the best that can be expected. When

δ

ε

E

is of the order of the machine precision, the errors in the result will be somewhat larger.

For small

x

, positive or negative, errors are strongly attenuated by the function and hence will be roughly bounded by the machine precision.

For moderate to large negative

x

, the error, like the function, is oscillatory; however, the amplitude of the error grows like

\frac{{| x |}^{7 / 4}}{\sqrt{π}} .

Therefore, it becomes impossible to calculate the function with any accuracy if

{| x |}^{7 / 4} > \frac{\sqrt{π}}{δ}

For large positive

x

, the relative error amplification is considerable:

\frac{ε}{δ} ≃ \sqrt{x^{3}} .

However, very large arguments are not possible due to the danger of underflow. Thus in practice error amplification is limited.

8 Parallelism and Performance

s17ajc is not threaded in any implementation.

9 Further Comments

None.

10 Example

This example reads values of the argument

x

from a file, evaluates the function at each value of

x

and prints the results.

s17aj: FL CL CPP AD

NAG CL Interfaces17ajc (airy_​ai_​deriv)

▸▿ Contents

1 Purpose

2 Specification

3 Description

4 References

5 Arguments

6 Error Indicators and Warnings

7 Accuracy

8 Parallelism and Performance

9 Further Comments

10 Example

10.1 Program Text

10.2 Program Data

10.3 Program Results

NAG CL Interface
s17ajc (airy_ai_deriv)