erfcx

Scaled complementary error function.

The scaled complementary error function is defined as

For large values, the scaled complementary error function is approximately equal to

Installation

npm install @stdlib/math-base-special-erfcx

Usage

var erfcx = require( '@stdlib/math-base-special-erfcx' );

erfcx( x )

Evaluates the scaled complementary error function.

var y = erfcx( 0.0 );
// returns 1.0

y = erfcx( 1.0 );
// returns ~0.4276

y = erfcx( -1.0 );
// returns ~5.01

y = erfcx( 50.0 );
// returns ~0.011

y = erfcx( -50.0 );
// returns +Infinity

If provided NaN, the function returns NaN.

var y = erfcx( NaN );
// returns NaN

Examples

var uniform = require( '@stdlib/random-array-uniform' );
var logEachMap = require( '@stdlib/console-log-each-map' );
var erfcx = require( '@stdlib/math-base-special-erfcx' );

var opts = {
    'dtype': 'float64'
};
var x = uniform( 100, -30.0, 30.0, opts );

logEachMap( 'x: %0.4f, erfcx(x): %0.4f', x, erfcx );

C APIs

Usage

#include "stdlib/math/base/special/erfcx.h"

stdlib_base_erfcx( x )

Evaluates the scaled complementary error function.

double y  = stdlib_base_erfcx( 0.0 );
// returns 1.0

y  = stdlib_base_erfcx( 1.0 );
// returns ~0.4276

The function accepts the following arguments:

• x: [in] double input value.

double stdlib_base_erfcx( const double x );

Examples

#include "stdlib/math/base/special/erfcx.h"
#include <stdio.h>

int main( void ) {
    const double x[] = { 0.0, 0.22, 0.44, 0.67, 0.89, 1.11, 1.33, 1.56, 1.78, 2.0 };

    double v;
    int i;
    for ( i = 0; i < 10; i++ ) {
        v = stdlib_base_erfcx( x[ i ] );
        printf( "x: %lf, erfcx(x): %lf\n", x[ i ], v );
    }
}

See Also

• @stdlib/math-base/special/erfc: complementary error function.
• @stdlib/math-base/special/erfcinv: inverse complementary error function.
• @stdlib/math-base/special/erf: error function.
• @stdlib/math-base/special/erfinv: inverse error function.

Notice

This package is part of stdlib, a standard library for JavaScript and Node.js, with an emphasis on numerical and scientific computing. The library provides a collection of robust, high performance libraries for mathematics, statistics, streams, utilities, and more.

For more information on the project, filing bug reports and feature requests, and guidance on how to develop stdlib, see the main project repository.

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Copyright

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