NAG CL Interfaces15abc (cdf_​normal)

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1Purpose

s15abc returns the value of the cumulative Normal distribution function, $P\left(x\right)$.

2Specification

 #include
 double s15abc (double x)
The function may be called by the names: s15abc, nag_specfun_cdf_normal or nag_cumul_normal.

3Description

s15abc evaluates an approximate value for the cumulative Normal distribution function
 $P(x) = 12π ∫-∞x e-u2/2 du .$
The function is based on the fact that
 $P(x) = 12 erfc(-x2)$
and it calls s15adc to obtain a value of $\mathit{erfc}$ for the appropriate argument.

4References

NIST Digital Library of Mathematical Functions

5Arguments

1: $\mathbf{x}$double Input
On entry: the argument $x$ of the function.

None.

7Accuracy

Because of its close relationship with $\mathit{erfc}$, the accuracy of this function is very similar to that in s15adc. If $\epsilon$ and $\delta$ are the relative errors in result and argument, respectively, they are in principle related by
 $|ε|≃ | x e -12 x2 2πP(x) δ|$
so that the relative error in the argument, $x$, is amplified by a factor, $\frac{x{e}^{-\frac{1}{2}{x}^{2}}}{\sqrt{2\pi }P\left(x\right)}$, in the result.
For $x$ small and for $x$ positive this factor is always less than $1$ and accuracy is mainly limited by machine precision.
For large negative $x$ the factor behaves like $\text{}\sim {x}^{2}$ and hence to a certain extent relative accuracy is unavoidably lost.
However, the absolute error in the result, $E$, is given by
 $|E|≃ | x e -12 x2 2π δ|$
so absolute accuracy can be guaranteed for all $x$.

8Parallelism and Performance

s15abc is not threaded in any implementation.

None.

10Example

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

10.1Program Text

Program Text (s15abce.c)

10.2Program Data

Program Data (s15abce.d)

10.3Program Results

Program Results (s15abce.r)