Measures of Central Tendency And Dispersion: A JavaScript library for probability & statistics
About
mctad.js is a JavaScript library for probability and statistics. A goal is to provide functionality missing from
other such libraries, including the ability to generate random variables from many common discrete and continuous
probability distributions, and having a basic implementation of directional statistics.
Use
You'll want either the file mctad.min.js or the file mctad.js in the root of this repository.
Documentation
See the GitHub pages for examples of using mctad.js. In addition,
mctad.js runs groc as a grunt task to automatically generate
html documentation from comments in the source code. Access that documentation by opening a browser on your local copy of
/doc/index.html after you git clone this repository or look at the /doc/
directory of the GitHub pages.
Continuous and Discrete Probability Distributions
Distributions can be called by their common names and required parameters, e.g., mctad.poisson(7). This returns an
object containing:
statistics on the distribution, including
mean
median
mode
variance
skewness
entropy
pdf, the probability density function (continuous distributions), or pmf, the probability mass function
(discrete distributions)
cdf, the cumulativedistributionfunction
convenience methods to access pmf as P(X) and cdf as F(X)
generate(n), a method for generating n random variables from the distribution
making it possible to say things such as
mctad.poisson(7).mean
mctad.poisson(7).P(5)
mctad.poisson(7).F(2)
mctad.triangular(3, 9, 4).generate(36)
mctad.normal(60.2, 4.5).generate(100)
Statistics on the distributions will return undefined if not implemented (this is version 0.0.X after all ) or if
actually not defined for the distribution. Since there need not be a single mode, mode always returns an Array.
Tests
mctad.js uses mocha with chai assertions as a grunt task to run the test suite. The
general format of the tests is to test exceptions before testing functionality. When possible, test data is taken from a
wikipedia article or other hopefully long-lived reference. If these are not available, hand-worked examples are used for
testing.
Conventions
The ability to use Greek letters directly in code appeals to me, and they are used internally. I am still considering
the extent to which they should be exposed externally. In an ideal world, it would be reliable to use constructions such
as p-hat (p̂) and x-bar (x̄) as variable names.
You will come across examples of type hinting, e.g., in the form of 1 versus 1.0, to help clarify whether quantities
are expected to take integer or real values.
mctad.js
Measures of Central Tendency And Dispersion: A JavaScript library for probability & statistics
About
mctad.js is a JavaScript library for probability and statistics. A goal is to provide functionality missing from other such libraries, including the ability to generate random variables from many common discrete and continuous probability distributions, and having a basic implementation of directional statistics.
Use
You'll want either the file
mctad.min.jsor the filemctad.jsin the root of this repository.Documentation
See the GitHub pages for examples of using mctad.js. In addition, mctad.js runs groc as a grunt task to automatically generate html documentation from comments in the source code. Access that documentation by opening a browser on your local copy of
/doc/index.htmlafter yougit clonethis repository or look at the/doc/directory of the GitHub pages.Continuous and Discrete Probability Distributions
Distributions can be called by their common names and required parameters, e.g.,
mctad.poisson(7). This returns an object containing:statistics on the distribution, including
pdf, the probability density function (continuous distributions), or pmf, the probability mass function (discrete distributions)
making it possible to say things such as
mctad.poisson(7).meanmctad.poisson(7).P(5)mctad.poisson(7).F(2)mctad.triangular(3, 9, 4).generate(36)mctad.normal(60.2, 4.5).generate(100)Statistics on the distributions will return
undefinedif not implemented (this is version 0.0.X after all ) or if actually not defined for the distribution. Since there need not be a single mode,modealways returns an Array.Tests
mctad.js uses mocha with chai assertions as a grunt task to run the test suite. The general format of the tests is to test exceptions before testing functionality. When possible, test data is taken from a wikipedia article or other hopefully long-lived reference. If these are not available, hand-worked examples are used for testing.
Conventions
The ability to use Greek letters directly in code appeals to me, and they are used internally. I am still considering the extent to which they should be exposed externally. In an ideal world, it would be reliable to use constructions such as p-hat (p̂) and x-bar (x̄) as variable names.
You will come across examples of type hinting, e.g., in the form of 1 versus 1.0, to help clarify whether quantities are expected to take integer or real values.
To Do