Moment-Generating Function

Bernoulli distribution moment-generating function (MGF).

The moment-generating function for a Bernoulli random variable is

upper M Subscript upper X Baseline left-parenthesis t right-parenthesis colon equals double-struck upper E left-bracket e Superscript t upper X Baseline right-bracket equals 1 minus p plus p exp left-parenthesis t right-parenthesis

where 0 <= p <= 1 is the success probability.

Usage

var mgf = require( '@stdlib/stats/base/dists/bernoulli/mgf' );

mgf( t, p )

Evaluates the moment-generating function (MGF) of a Bernoulli distribution with success probability p.

var y = mgf( 0.2, 0.5 );
// returns ~1.111

y = mgf( 0.4, 0.5 );
// returns ~1.246

If provided NaN as any argument, the function returns NaN.

var y = mgf( NaN, 0.0 );
// returns NaN

y = mgf( 0.0, NaN );
// returns NaN

If provided a success probability p outside of the interval [0,1], the function returns NaN.

var y = mgf( -2.0, -1.0 );
// returns NaN

y = mgf( 0.2, 2.0 );
// returns NaN

mgf.factory( p )

Returns a function for evaluating the moment-generating function of a Bernoulli distribution with parameter p (success probability).

var mymgf = mgf.factory( 0.8 );
var y = mymgf( -0.2 );
// returns ~0.855

Examples

var randu = require( '@stdlib/random/base/randu' );
var mgf = require( '@stdlib/stats/base/dists/bernoulli/mgf' );

var p;
var t;
var y;
var i;

for ( i = 0; i < 10; i++ ) {
    t = ( randu() * 4.0 ) - 2.0;
    p = randu();
    y = mgf( t, p );
    console.log( 't: %d, p: %d, M_X(t;p): %d', t, p.toFixed( 4 ), y.toFixed( 4 ) );
}
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