Mean
Geometric distribution expected value.
The expected value for a geometric random variable is
where 0 <= p <= 1
is the success probability. The random variable X
denotes the number of failures until the first success in a sequence of independent Bernoulli trials.
Installation
$ npm install distributions-geometric-mean
For use in the browser, use browserify.
Usage
var mean = ;
mean( p[, opts] )
Computes the expected value for a geometric distribution with parameter p
. p
may be either a number
, an array
, a typed array
, or a matrix
.
var matrix =pmatouti;out = ;// returns 4p = 02 04 08 1 ;out = ;// returns [ 4, 1.5, 0.25, 0 ]p = p ;out = ;// returns Float64Array( [4,1.5,0.25,0] )p = ;/*[ 0.2 0.40.8 1 ]*/out = ;/*[ 4 1.50.25 0 ]*/
The function accepts the following options
:
- accessor: accessor
function
for accessingarray
values. - dtype: output
typed array
ormatrix
data type. Default:float64
. - copy:
boolean
indicating if thefunction
should return a new data structure. Default:true
. - path: deepget/deepset key path.
- sep: deepget/deepset key path separator. Default:
'.'
.
For non-numeric arrays
, provide an accessor function
for accessing array
values.
var p =00210420831;{return d 1 ;}var out =;// returns [ 4, 1.5, 0.25, 0 ]
To deepset an object array
, provide a key path and, optionally, a key path separator.
var p ='x':902'x':904'x':908'x':91;var out =;/*[ { x: [ 9, 4 ] },{ x: [ 9, 1.5 ] },{ x: [ 9, 0.25 ] },{ x: [ 9, 0 ] } ]*/var bool = p === out ;// returns true
By default, when provided a typed array
or matrix
, the output data structure is float64
in order to preserve precision. To specify a different data type, set the dtype
option (see matrix
for a list of acceptable data types).
var p out;p = 0204081 ;out =;// returns Int32Array( [4,1,0,0] )// Works for plain arrays, as well...out =;// returns Int32Array( [4,1,0,0] )
By default, the function returns a new data structure. To mutate the input data structure (e.g., when input values can be discarded or when optimizing memory usage), set the copy
option to false
.
var pboolmatouti;p = 02 04 08 1 ;out =;// returns [ 4, 1.5, 0.25, 0 ]bool = p === out ;// returns truemat = ;/*[ 0.2 0.40.8 1 ]*/out =;/*[ 4 1.50.25 0 ]*/bool = mat === out ;// returns true
Notes
-
If an element is not a number in the interval [0,1], the expected value is
NaN
.var p out;out = ;// returns NaNout = ;// returns NaNout = ;// returns NaNout = ;// returns NaNout = ;// returns NaNout = ;// returns [ NaN, NaN, NaN ]{return dx;}p ='x':true'x':'x':{}'x':null;out =;// returns [ NaN, NaN, NaN, NaN ]out =;/*[{'x':NaN},{'x':NaN},{'x':NaN,{'x':NaN}]*/ -
Be careful when providing a data structure which contains non-numeric elements and specifying an
integer
output data type, asNaN
values are cast to0
.var out =;// returns Int8Array( [0,0,0] );
Examples
var matrix =mean = ;var pmatouttmpi;// Plain arrays...p = 10 ;for i = 0; i < plength; i++p i = i / 10;out = ;// Object arrays (accessors)...{return dx;}for i = 0; i < plength; i++p i ='x': p i;out =;// Deep set arrays...for i = 0; i < plength; i++p i ='x': i p i x;out =;// Typed arrays...p = 10 ;for i = 0; i < plength; i++p i = i / 10;out = ;// Matrices...mat = ;out = ;// Matrices (custom output data type)...out =;
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,
$ make view-cov
License
Copyright
Copyright © 2015. The Compute.io Authors.