nag_airy_ai_deriv (s17ajc) returns a value of the derivative of the Airy function .
nag_airy_ai_deriv (s17ajc) evaluates an approximation to the derivative of the Airy function . It is based on a number of Chebyshev expansions.
For
,
where
,
and
and
are expansions in variable
.
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 , where is the machine precision.
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,
, and the relative error,
, are related in principle to the relative error in the argument,
, by
In practice, approximate equality is the best that can be expected. When
,
or
is of the order of the
machine precision, the errors in the result will be somewhat larger.
For moderate to large negative
, the error, like the function, is oscillatory; however the amplitude of the error grows like
Therefore it becomes impossible to calculate the function with any accuracy if
.
For large positive
, the relative error amplification is considerable:
However, very large arguments are not possible due to the danger of underflow. Thus in practice error amplification is limited.
Not applicable.
None.