Logarithm of Probability Density Function

Lévy distribution logarithm of probability density function (PDF).

The probability density function (PDF) for a Lévy random variable is

f left-parenthesis x semicolon mu comma c right-parenthesis equals StartLayout Enlarged left-brace 1st Row 1st Column StartRoot StartFraction c Over 2 pi EndFraction EndRoot StartFraction e Superscript minus StartFraction c Over 2 left-parenthesis x minus mu right-parenthesis EndFraction Baseline Over left-parenthesis x minus mu right-parenthesis Superscript 3 slash 2 Baseline EndFraction 2nd Column for x greater-than mu 2nd Row 1st Column 0 2nd Column otherwise EndLayout

where μ is the location parameter and c > 0 is the scale parameter.

Usage

var logpdf = require( '@stdlib/stats/base/dists/levy/logpdf' );

logpdf( x, mu, c )

Evaluates the logarithm of the probability density function (PDF) for a Lévy distribution with parameters mu (location parameter) and c (scale parameter).

var y = logpdf( 2.0, 0.0, 1.0 );
// returns ~-2.209

y = logpdf( -1.0, 4.0, 4.0 );
// returns -Infinity

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

var y = logpdf( NaN, 0.0, 1.0 );
// returns NaN

y = logpdf( 0.0, NaN, 1.0 );
// returns NaN

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

If provided c <= 0, the function returns NaN.

var y = logpdf( 2.0, 0.0, -1.0 );
// returns NaN

y = logpdf( 2.0, 0.0, 0.0 );
// returns NaN

logpdf.factory( mu, c )

Returns a function for evaluating the logarithm of the probability density function (PDF) of a Lévy distribution with parameters mu (location parameter) and c (scale parameter).

var mylogpdf = logpdf.factory( 10.0, 2.0 );

var y = mylogpdf( 11.0 );
// returns ~-1.572

y = mylogpdf( 20.0 );
// returns ~-4.126

Notes

  • In virtually all cases, using the logpdf or logcdf functions is preferable to manually computing the logarithm of the pdf or cdf, respectively, since the latter is prone to overflow and underflow.

Examples

var randu = require( '@stdlib/random/base/randu' );
var EPS = require( '@stdlib/constants/float64/eps' );
var logpdf = require( '@stdlib/stats/base/dists/levy/logpdf' );

var mu;
var c;
var x;
var y;
var i;

for ( i = 0; i < 10; i++ ) {
    mu = randu() * 10.0;
    x = ( randu()*10.0 ) + mu;
    c = ( randu()*10.0 ) + EPS;
    y = logpdf( x, mu, c );
    console.log( 'x: %d, µ: %d, c: %d, ln(f(x;µ,c)): %d', x, mu, c, y );
}
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