|
||
---|---|---|
.. | ||
docs | ||
lib | ||
package.json | ||
README.md |
Logarithm of Probability Density Function
Cauchy distribution logarithm of probability density function (logPDF).
The probability density function (PDF) for a Cauchy random variable is
where x0
is the location parameter and gamma > 0
is the scale parameter.
Usage
var logpdf = require( '@stdlib/stats/base/dists/cauchy/logpdf' );
logpdf( x, x0, gamma )
Evaluates the natural logarithm of the probability density function (PDF) for a Cauchy distribution with parameters x0
(location parameter) and gamma > 0
(scale parameter).
var y = logpdf( 2.0, 1.0, 1.0 );
// returns ~-1.838
y = logpdf( 4.0, 3.0, 0.1 );
// returns ~-3.457
y = logpdf( 4.0, 3.0, 3.0 );
// returns ~-2.349
If provided NaN
as any argument, the function returns NaN
.
var y = logpdf( NaN, 1.0, 1.0 );
// returns NaN
y = logpdf( 2.0, NaN, 1.0 );
// returns NaN
y = logpdf( 2.0, 1.0, NaN );
// returns NaN
If provided gamma <= 0
, the function returns NaN
.
var y = logpdf( 2.0, 0.0, -1.0 );
// returns NaN
logpdf.factory( x0, gamma )
Returns a function
for evaluating the natural logarithm of the PDF of a Cauchy distribution with location parameter x0
and scale parameter gamma
.
var mylogpdf = logpdf.factory( 10.0, 2.0 );
var y = mylogpdf( 10.0 );
// returns ~-1.838
y = mylogpdf( 5.0 );
// returns ~-3.819
Notes
- In virtually all cases, using the
logpdf
orlogcdf
functions is preferable to manually computing the logarithm of thepdf
orcdf
, 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/cauchy/logpdf' );
var gamma;
var x0;
var x;
var y;
var i;
for ( i = 0; i < 10; i++ ) {
x = randu() * 10.0;
x0 = ( randu()*10.0 ) - 5.0;
gamma = ( randu()*20.0 ) + EPS;
y = logpdf( x, gamma, x0 );
console.log( 'x: %d, x0: %d, γ: %d, ln(f(x;x0,γ)): %d', x.toFixed(4), x0.toFixed(4), gamma.toFixed(4), y.toFixed(4) );
}