Exponential distribution standard deviation.
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[Exponential][exponential-distribution] distribution [standard deviation][standard-deviation].
math
\sigma = \lambda^{-1}
λ
is the rate parameter.bash
npm install @stdlib/stats-base-dists-exponential-stdev
script
tag without installation and bundlers, use the [ES Module][es-module] available on the [esm
][esm-url] branch (see [README][esm-readme]).deno
][deno-url] branch (see [README][deno-readme] for usage intructions).umd
][umd-url] branch (see [README][umd-readme]).javascript
var stdev = require( '@stdlib/stats-base-dists-exponential-stdev' );
lambda
.javascript
var v = stdev( 9.0 );
// returns ~0.11
v = stdev( 0.5 );
// returns 2.0
lambda < 0
, the function returns NaN
.javascript
var v = stdev( -1.0 );
// returns NaN
javascript
var randu = require( '@stdlib/random-base-randu' );
var round = require( '@stdlib/math-base-special-round' );
var stdev = require( '@stdlib/stats-base-dists-exponential-stdev' );
var lambda;
var v;
var i;
for ( i = 0; i < 10; i++ ) {
lambda = randu() * 20.0;
v = stdev( lambda );
console.log( 'λ: %d, SD(X;λ): %d', lambda.toFixed( 4 ), v.toFixed( 4 ) );
}
c
#include "stdlib/stats/base/dists/exponential/stdev.h"
c
double out = stdlib_base_dists_exponential_stdev( 9.0 );
// returns ~0.111
[in] double
rate parameter.c
double stdlib_base_dists_exponential_stdev( const double lambda );
c
#include "stdlib/stats/base/dists/exponential/stdev.h"
#include <stdlib.h>
#include <stdio.h>
static double random_uniform( const double min, const double max ) {
double v = (double)rand() / ( (double)RAND_MAX + 1.0 );
return min + ( v*(max-min) );
}
int main( void ) {
double lambda;
double y;
int i;
for ( i = 0; i < 25; i++ ) {
lambda = random_uniform( 0.0, 20.0 );
y = stdlib_base_dists_exponential_stdev( lambda );
printf( "λ: %lf, SD(X;λ): %lf\n", lambda, y );
}
}