Normal
Normal distribution.
Installation
$ npm install distributions-normal
For use in the browser, use browserify.
Usage
To use the module,
var createDist = ;
To create a normal distribution,
var normal = ;
The distribution is configurable and has the following methods...
normal.support()
Returns the distribution support, which is the set of all real values.
var support = normal;// returns [-inf, inf]
normal.mean( [value] )
This method is a setter/getter. If no value
is provided, returns the distribution mean
. To set the distribution mean
,
normal;
The default distribution mean
is 0.
normal.variance( [value] )
This method is a setter/getter. If no value
is provided, returns the distribution variance
. To set the distribution variance
,
normal;
The default distribution variance
is 1.
normal.median()
Returns the distribution median
, which is equal to the distribution mean
.
var median = normal;// equals normal.mean()
normal.mode()
Returns the distribution mode
, which is equal to the distribution mean
.
var mode = normal;// equals normal.mean()
normal.skewness()
Returns the distribution skewness
, which is equal to 0.
var skewness = normal;// returns 0
normal.ekurtosis()
Returns the distribution excess kurtosis
, which is equal to 0.
var excess = normal;// returns 0
normal.information()
Returns the Fisher information.
var info = normal;// returns [...]
normal.entropy()
Returns the distribution's differential entropy.
var entropy = normal;// approx 1.42 for mu=0, variance=1
normal.pdf( [arr] )
If a vector is not provided, returns the probability density function (PDF). If a vector is provided, evaluates the PDF for each vector element.
var data = -1 -05 0 05 1 ;var pdf = normal;// returns [...]
normal.cdf( [arr] )
If a vector is not provided, returns the cumulative density function (CDF). If a vector is provided, evaluates the CDF for each vector element.
var data = -1 -05 0 05 1 ;var cdf = normal;// returns [...]
normal.inv( [arr] )
If a cumulative probability vector is not provided, returns the inverse cumulative distribution function (aka the quantile function). If a cumulative probability vector is provided, evaluates the quantile function for each vector element.
var probs = 0025 05 0975 ;var quantiles = normal;// returns [...]
Note: all vector values must exist on the interval [0, 1]
.
Examples
var createDist =median =mean = ;// Define the distribution parameters...var mu = 100s2 = 25xLow = 0xHigh = 200;// Create a vector...var vec = 1000len = veclengthinc;inc = xHigh - xLow / len;for var i = 0; i < len; i++vec i = inc*i + xLow;// Create a normal distribution and configure...var normal =;// Evaluate the probability density function over the vector...var pdf = normal;// Find the max...var max = pdf 0idx = 0;for var j = 1; j < pdflength; j++if pdf j > maxmax = pdf j ;idx = j;console;// Calculate the median...console;// Calculate the mean...console;// Evaluate the quantile function for canonical cumulative probability values...var quantiles = normal;console;
To run the example code from the top-level application directory,
$ node ./examples/index.js
Tests
Unit
Unit tests use the Mocha test framework with Chai assertions. To run the tests, execute the following command in the top-level application directory:
$ make test
All new feature development should have corresponding unit tests to validate correct functionality.
Test Coverage
This repository uses Istanbul as its code coverage tool. To generate a test coverage report, execute the following command in the top-level application directory:
$ make test-cov
Istanbul creates a ./reports/coverage
directory. To access an HTML version of the report,
$ open reports/coverage/lcov-report/index.html
License
Copyright
Copyright © 2014. Athan Reines.