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Evaluate the logarithm of the cumulative distribution function Planck (discrete exponential) distribution.
The cumulative distribution function for a Planck random variable is
where λ is the shape parameter and x denotes the count of events in a quantized system.
import logcdf from 'https://cdn.jsdelivr.net/gh/stdlib-js/stats-base-dists-planck-logcdf@esm/index.mjs';The previous example will load the latest bundled code from the esm branch. Alternatively, you may load a specific version by loading the file from one of the tagged bundles. For example,
import logcdf from 'https://cdn.jsdelivr.net/gh/stdlib-js/stats-base-dists-planck-logcdf@v0.0.0-esm/index.mjs';You can also import the following named exports from the package:
import { factory } from 'https://cdn.jsdelivr.net/gh/stdlib-js/stats-base-dists-planck-logcdf@esm/index.mjs';Evaluates the logarithm of the cumulative distribution function for a Planck (discrete exponential) distribution with shape parameter lambda.
var y = logcdf( 2.0, 0.5 );
// returns ~-0.2525
y = logcdf( 2.0, 1.5 );
// returns ~-0.0112If provided NaN as any argument, the function returns NaN.
var y = logcdf( NaN, 0.5 );
// returns NaN
y = logcdf( 0.0, NaN );
// returns NaNIf provided a shape parameter lambda which is nonpositive, the function returns NaN.
var y = logcdf( 2.0, -1.0 );
// returns NaNReturns a function for evaluating the logarithm of the cumulative distribution function of a Planck (discrete exponential) distribution with shape parameter lambda.
var mylogcdf = logcdf.factory( 1.5 );
var y = mylogcdf( 3.0 );
// returns ~-0.0025
y = mylogcdf( 1.0 );
// returns ~-0.0511- In virtually all cases, using the
logpmforlogcdffunctions is preferable to manually computing the logarithm of thepmforcdf, respectively, since the latter is prone to overflow and underflow.
<!DOCTYPE html>
<html lang="en">
<body>
<script type="module">
import discreteUniform from 'https://cdn.jsdelivr.net/gh/stdlib-js/random-array-discrete-uniform@esm/index.mjs';
import uniform from 'https://cdn.jsdelivr.net/gh/stdlib-js/random-array-uniform@esm/index.mjs';
import logcdf from 'https://cdn.jsdelivr.net/gh/stdlib-js/stats-base-dists-planck-logcdf@esm/index.mjs';
var x = discreteUniform( 10, 0, 5 );
var lambda = uniform( 10, 0.1, 5.0 );
var y;
var i;
for ( i = 0; i < lambda.length; i++ ) {
y = logcdf( x[ i ], lambda[ i ] );
console.log( 'x: %d, λ: %d, ln(F(x;λ)): %d', x[ i ].toFixed( 4 ), lambda[ i ].toFixed( 4 ), y.toFixed( 4 ) );
}
</script>
</body>
</html>This package is part of stdlib, a standard library with an emphasis on numerical and scientific computing. The library provides a collection of robust, high performance libraries for mathematics, statistics, streams, utilities, and more.
For more information on the project, filing bug reports and feature requests, and guidance on how to develop stdlib, see the main project repository.
See LICENSE.
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