Package Exports
- @stdlib/stats-base-dists-t-ctor
- @stdlib/stats-base-dists-t-ctor/dist
- @stdlib/stats-base-dists-t-ctor/dist/index.js
- @stdlib/stats-base-dists-t-ctor/lib/index.js
This package does not declare an exports field, so the exports above have been automatically detected and optimized by JSPM instead. If any package subpath is missing, it is recommended to post an issue to the original package (@stdlib/stats-base-dists-t-ctor) to support the "exports" field. If that is not possible, create a JSPM override to customize the exports field for this package.
Readme
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Student's T
Student's t distribution constructor.
Installation
npm install @stdlib/stats-base-dists-t-ctor
Usage
var T = require( '@stdlib/stats-base-dists-t-ctor' );
T( [v] )
Returns a Student's t distribution object.
var t = new T();
var mu = t.mean;
// returns NaN
By default, v = 1.0
. To create a distribution having a different degrees of freedom v
, provide a parameter value.
var t = new T( 4.0 );
var mu = t.mean;
// returns 0.0
t
A Student's t distribution object has the following properties and methods...
Writable Properties
t.v
Degrees of freedom of the distribution. v
must be a positive number.
var t = new T( 2.0 );
var v = t.v;
// returns 2.0
t.v = 3.0;
v = t.v;
// returns 3.0
Computed Properties
T.prototype.entropy
Returns the differential entropy.
var t = new T( 4.0 );
var entropy = t.entropy;
// returns ~1.682
T.prototype.kurtosis
Returns the excess kurtosis.
var t = new T( 4.0 );
var kurtosis = t.kurtosis;
// returns Infinity
T.prototype.mean
Returns the expected value.
var t = new T( 4.0 );
var mu = t.mean;
// returns 0.0
T.prototype.median
Returns the median.
var t = new T( 4.0 );
var median = t.median;
// returns 0.0
T.prototype.mode
Returns the mode.
var t = new T( 4.0 );
var mode = t.mode;
// returns 0.0
T.prototype.skewness
Returns the skewness.
var t = new T( 4.0 );
var skewness = t.skewness;
// returns 0.0
T.prototype.stdev
Returns the standard deviation.
var t = new T( 4.0 );
var s = t.stdev;
// returns ~1.414
T.prototype.variance
Returns the variance.
var t = new T( 4.0 );
var s2 = t.variance;
// returns 2.0
Methods
T.prototype.cdf( x )
Evaluates the cumulative distribution function (CDF).
var t = new T( 2.0 );
var y = t.cdf( 0.5 );
// returns ~0.667
T.prototype.logcdf( x )
Evaluates the natural logarithm of the cumulative distribution function (CDF).
var t = new T( 2.0 );
var y = t.logcdf( 0.5 );
// returns ~-0.405
T.prototype.logpdf( x )
Evaluates the natural logarithm of the probability density function (PDF).
var t = new T( 2.0 );
var y = t.logpdf( 0.8 );
// returns ~-1.456
T.prototype.pdf( x )
Evaluates the probability density function (PDF).
var t = new T( 2.0 );
var y = t.pdf( 0.8 );
// returns ~0.233
T.prototype.quantile( p )
Evaluates the quantile function at probability p
.
var t = new T( 2.0 );
var y = t.quantile( 0.5 );
// returns 0.0
y = t.quantile( 1.9 );
// returns NaN
Examples
var T = require( '@stdlib/stats-base-dists-t-ctor' );
var t = new T( 2.0 );
var mu = t.mean;
// returns 0.0
var mode = t.mode;
// returns 0.0
var s2 = t.variance;
// returns Infinity
var y = t.cdf( 0.8 );
// returns ~0.746
Notice
This package is part of stdlib, a standard library for JavaScript and Node.js, 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.
Community
License
See LICENSE.
Copyright
Copyright © 2016-2024. The Stdlib Authors.