# logaddexp
> Evaluates the [natural logarithm][@stdlib/math/base/special/ln] of `exp(x) + exp(y)`.
Log-domain computations are commonly used to increase accuracy and avoid underflow and overflow when very small or very large numbers are represented directly as limited-precision, floating-point numbers. For example, in statistics, evaluating `logaddexp()` is useful when probabilities are so small as to exceed the normal range of floating-point numbers.
## Usage
```javascript
var logaddexp = require( '@stdlib/math/base/special/logaddexp' );
```
#### logaddexp( x, y )
Evaluates the [natural logarithm][@stdlib/math/base/special/ln] of `exp(x) + exp(y)`.
```javascript
var v = logaddexp( 90.0, 90.0 );
// returns ~90.6931
v = logaddexp( -20.0, 90.0 );
// returns 90.0
v = logaddexp( 0.0, -100.0 );
// returns ~3.7201e-44
v = logaddexp( NaN, 1.0 );
// returns NaN
```
## Examples
```javascript
var incrspace = require( '@stdlib/array/incrspace' );
var logaddexp = require( '@stdlib/math/base/special/logaddexp' );
var x;
var v;
var i;
var j;
x = incrspace( -100.0, 100.0, 1.0 );
for ( i = 0; i < x.length; i++ ) {
for ( j = i; j < x.length; j++ ) {
v = logaddexp( x[ i ], x[ j ] );
console.log( 'x: %d, y: %d, f(x, y): %d', x[ i ], x[ j ], v );
}
}
```
[@stdlib/math/base/special/ln]: https://www.npmjs.com/package/@stdlib/math/tree/main/base/special/ln