statty.js
v1.0.1
Published
JavaScript Probability and Statistics
Downloads
5
Maintainers
Readme
statty.js
Statistics for javascript
Intended for node.js
. Available through npm.
###Installation
npm install statty.js
Or clone the repo and put it in your project.
###Setup
var stats = require('statty.js')
console.log(stats.normal(5,1).rand())
So far the only distributions are the normal
, uniform
, laplace
, poisson
, pareto
, exponential
, geometric
, bernoulli
, and binomial
. In general, each distribution is initalized with the parameters listed on Wikipedia, in the order listed there. When using the fit
method, which is available for all distributions expcept the binomial
, parameters are calculated using the Maximum Likelihood Estimator for the distribution.
#####Examples
var stats = require('statty.js')
norm = stats.normal(5,1) \\ normal with mean 5, variance 1
unif = stats.uniform(10,20) \\ uniform from range 10 to 20
pare = stats.pareto(1,6/5) \\ pareto with scale 1 and shape 1.2
lapl = stats.laplace(10,4) \\ laplace with mean 10, scale 4
geom = stats.geometric(.5) \\ geometric with sucess .5
pois = stats.poisson(10) \\ poisson with mean 10
expo = stats.exponential(1/10) \\ exponential with mean 10
bern = stats.bernoulli(.7) \\ bernoulli with mean .7
bino = stats.binomial(10,.7) \\ binomial with 10 trials, probability .7
console.log(norm.pdf(1)) \\ probability density function
console.log(bern.pmf(1)) \\ discrete distributions have pmf
console.log(norm.cdf(4)) \\ cumulative density function
console.log(norm.quantile(.9)) \\ quantile
console.log(bern.rand()) \\ generates a random bernoulli trial
\\or
norm = stats.normal.fit([1,2,3,4]) \\ returns model fitted to data
console.log(norm.mean) \\ mean attribute (calculated for uniform)
console.log(norm.variance) \\ variance attribute (calculated for uniform)
console.log(norm.rand(10)) \\ generates array of 10 random numbers