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Hernán Morales Durand
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Merge branch 'PolyMathOrg:master' into iss_reverse_binomial
2 parents 2e93965 + d93dfc5 commit 2e5da94

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‎.github/workflows/smalltalk-ci.yml‎

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name: CI matrix
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on:
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push:
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branches: [ master ]
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pull_request:
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branches: [ master ]
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# Allows you to run this workflow manually from the Actions tab
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workflow_dispatch:
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# A workflow run is made up of one or more jobs that can run sequentially or in parallel
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jobs:
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build:
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strategy:
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matrix:
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os: [ macos-latest, windows-latest, ubuntu-latest]
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smalltalk: [ Pharo64-8.0 ]
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runs-on: ${{ matrix.os }}
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name: ${{ matrix.smalltalk }} on ${{ matrix.os }}
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steps:
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- uses: actions/checkout@v2
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- name: Setup smalltalkCI
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uses: hpi-swa/setup-smalltalkCI@v1
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with:
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smalltalk-image: ${{ matrix.smalltalk }}
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- name: Load Image and Run Tests
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run: smalltalkci -s ${{ matrix.smalltalk }}
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env:
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GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
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timeout-minutes: 15

‎.travis.yml‎

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‎README.md‎

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</p>
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</p>
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[![Pharo version](https://img.shields.io/badge/Pharo-7.0-%23aac9ff.svg)](https://pharo.org/download)
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[![Pharo version](https://img.shields.io/badge/Pharo-8.0-%23aac9ff.svg)](https://pharo.org/download)
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[![Build Status](https://travis-ci.org/PolyMathOrg/PolyMath.svg?branch=master)](https://travis-ci.org/PolyMathOrg/PolyMath)
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[![Build status](https://ci.appveyor.com/api/projects/status/3tvarh2xi22max8h?svg=true)](https://ci.appveyor.com/project/SergeStinckwich/polymath-88bea)
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[![CI matrix](https://github.com/PolyMathOrg/PolyMath/actions/workflows/smalltalk-ci.yml/badge.svg)](https://github.com/PolyMathOrg/PolyMath/actions/workflows/smalltalk-ci.yml)
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[![Coverage Status](https://coveralls.io/repos/github/PolyMathOrg/PolyMath/badge.svg?branch=master)](https://coveralls.io/github/PolyMathOrg/PolyMath?branch=master)
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[![License](https://img.shields.io/badge/license-MIT-blue.svg)](https://raw.githubusercontent.com/PolyMathOrg/PolyMath/master/LICENSE)
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<img width="1675" alt="Screenshot 2019-04-24 at 11 12 57" src="https://user-images.githubusercontent.com/327334/56652094-66eb7780-6682-11e9-9753-101be18df67c.png">
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You can load PolyMath 1.0.2 into a fresh Pharo 8.0 image with:
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You can load PolyMath 1.0.3 into a fresh Pharo 8.0 image with:
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```Smalltalk
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Metacello new
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repository: 'github://PolyMathOrg/PolyMath:v1.0.2';
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repository: 'github://PolyMathOrg/PolyMath:v1.0.3';
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baseline: 'PolyMath';
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load
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```

‎appveyor.yml‎

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‎src/BaselineOfPolyMath/BaselineOfPolyMath.class.st‎

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@@ -113,6 +113,8 @@ BaselineOfPolyMath >> baseline: spec [
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with: [ spec requires: #('Math-Complex') ];
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package: 'Math-Tests-Core'
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with: [ spec requires: #('Math-Core') ];
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package: 'Math-Tests-Core-Distribution'
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with: [ spec requires: #('Math-Core-Distribution') ];
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package: 'Math-Tests-Core-Process'
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with: [ spec requires: #('Math-Core-Process') ];
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package: 'Math-Tests-Numerical'
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#('Math-Clustering' 'Math-Number-Extensions' 'Math-Chromosome' 'Math-PrincipalComponentAnalysis' 'Math-FunctionFit' 'Math-AutomaticDifferenciation' 'Math-KernelSmoothing' 'Math-Permutation' 'Math-KolmogorovSmirnov');
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group: 'Tests'
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with:
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#('Math-Tests-Matrix' 'Math-Tests-Clustering' 'Math-Tests-Numerical' 'Math-Tests-Complex' 'Math-Tests-Quaternion' 'Math-Tests-Random' 'Math-Tests-ODE' 'Math-Tests-KDTree' 'Math-Tests-FunctionFit' 'Math-Tests-AutomaticDifferenciation' 'Math-Tests-FastFourierTransform' 'Math-Tests-Accuracy' 'Math-Tests-ArbitraryPrecisionFloat' 'Math-Tests-KolmogorovSmirnov' 'Math-Tests-Quantile' 'Math-Tests-Polynomials' 'Math-Tests-PrincipalComponentAnalysis' 'Math-Tests-KernelSmoothing' 'Math-Tests-Number-Extensions' 'Math-Tests-Permutation' 'Math-Tests-TSNE' 'Math-Tests-Core-Process' 'Math-Tests-Core');
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#('Math-Tests-Matrix' 'Math-Tests-Clustering' 'Math-Tests-Numerical' 'Math-Tests-Complex' 'Math-Tests-Quaternion' 'Math-Tests-Random' 'Math-Tests-ODE' 'Math-Tests-KDTree' 'Math-Tests-FunctionFit' 'Math-Tests-AutomaticDifferenciation' 'Math-Tests-FastFourierTransform' 'Math-Tests-Accuracy' 'Math-Tests-ArbitraryPrecisionFloat' 'Math-Tests-KolmogorovSmirnov' 'Math-Tests-Quantile' 'Math-Tests-Polynomials' 'Math-Tests-PrincipalComponentAnalysis' 'Math-Tests-KernelSmoothing' 'Math-Tests-Number-Extensions' 'Math-Tests-Permutation' 'Math-Tests-TSNE' 'Math-Tests-Core-Process' 'Math-Tests-Core-Distribution' 'Math-Tests-Core');
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group: 'default'
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with: #('Core' 'Extensions' 'Tests' 'Benchmarks' 'Accuracy') ]
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]

‎src/Math-Complex/Number.extension.st‎

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aNumber isNumber ifFalse: [self error: 'Badly formed complex number'].
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^PMComplex real: self imaginary: aNumber
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]
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{ #category : #'*Math-Complex' }
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Number >> isComplexConjugateOf: aNumber [
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"A complex conjugate of a real number is same real number"
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^ self = aNumber
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]
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{ #category : #'*Math-Complex' }
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Number >> isComplexConjugateOfAComplexNumber: aComplexNumber [
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"A complex conjugate of a real number is same real number"
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^ self isComplexConjugateOf: aComplexNumber
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]
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{ #category : #'*Math-Complex' }
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Number >> isRealNumber [
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"Answer true if receiver is a real number. All instances of Number are real numbers."
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^ true
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]

‎src/Math-Complex/Object.extension.st‎

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^ false
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]
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{ #category : #'*Math-Complex' }
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Object >> isRealNumber [
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"Answer true if receiver is a real number. False by default."
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^ false
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]

‎src/Math-Complex/PMComplex.class.st‎

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^ imaginary
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]
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{ #category : #testing }
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PMComplex >> isComplexConjugateOf: aNumber [
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"Answer true if self and aNumber are complex conjugates of each other. The complex conjugate of a complex number is the number with an equal real part and an imaginary part equal in magnitude but opposite in sign."
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^ aNumber isComplexConjugateOfAComplexNumber: self
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]
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{ #category : #testing }
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PMComplex >> isComplexConjugateOfAComplexNumber: aComplexNumber [
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"Answer true if self and aComplexNumber are complex conjugates of each other. The complex conjugate of a complex number is the number with an equal real part and an imaginary part equal in magnitude but opposite in sign."
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^ (aComplexNumber real = real) and: [ aComplexNumber imaginary = (-1 * imaginary) ]
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]
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{ #category : #testing }
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PMComplex >> isComplexNumber [
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^ true

‎src/Math-Complex/PMComplex.extension.st‎

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^ aVector collect: [ :each | each * self ]
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]
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{ #category : #'*Math-Complex' }
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PMComplex class >> random [
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"Answers a random number with abs between 0 and 1."
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^ self abs: 1.0 random arg: 2 * Float pi random
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]
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{ #category : #'*Math-Complex' }
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PMComplex >> random [
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"analog to Number>>random. However, the only bound is that the abs of the produced complex is less than the length of the receive. The receiver effectively defines a disc within which the random element can be produced."
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^ self class random * self
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]
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{ #category : #'*Math-Complex' }
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PMComplex class >> random [
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"Answers a random number with abs between 0 and 1."
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^ self abs: 1.0 random arg: 2 * Float pi random
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]
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{ #category : #'*Math-Complex' }
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PMComplex >> subtractToPolynomial: aPolynomial [
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^ aPolynomial addNumber: self negated

‎src/Math-Core-Distribution/PMMultivariateNormalDistribution.class.st‎

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Class {
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#name : #PMMultivariateNormalDistribution,
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#superclass : #PMProbabilityDensity,
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#instVars : [
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'meanVector',
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'covarianceMatrix'
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],
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#category : #'Math-Core-Distribution'
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}
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{ #category : #'instance creation' }
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PMMultivariateNormalDistribution class >> meanVector: aMeanVector covarianceMatrix: aCovarianceMatrix [
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^ self new
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initializeMeanVector: aMeanVector
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covarianceMatrix: aCovarianceMatrix;
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yourself
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]
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{ #category : #information }
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PMMultivariateNormalDistribution >> average [
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^ self meanVector
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]
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{ #category : #transformation }
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PMMultivariateNormalDistribution >> changeParametersBy: aVector [
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"Modify the parameters of the receiver by aVector."
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meanVector := meanVector + aVector first.
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covarianceMatrix := covarianceMatrix + aVector second.
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]
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{ #category : #information }
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PMMultivariateNormalDistribution >> covarianceMatrix [
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^ covarianceMatrix
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]
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{ #category : #information }
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PMMultivariateNormalDistribution >> distributionValue: aNumber [
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"Answers the probability of observing a random variable distributed according to the receiver with a value lower than or equal to aNumber. Also known as the cumulative density function (CDF)."
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self shouldBeImplemented
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]
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{ #category : #initialization }
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PMMultivariateNormalDistribution >> initializeMeanVector: aMeanVector covarianceMatrix: aCovarianceMatrix [
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meanVector := aMeanVector.
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covarianceMatrix := aCovarianceMatrix.
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]
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{ #category : #information }
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PMMultivariateNormalDistribution >> kurtosis [
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"Kurtosis is a measure of the 'tailedness' of the probability distribution of a real-valued random variable. Not defined for a multivariate normal distribution"
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self shouldNotImplement
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]
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{ #category : #information }
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PMMultivariateNormalDistribution >> meanVector [
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^ meanVector
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]
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{ #category : #information }
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PMMultivariateNormalDistribution >> parameters [
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"Returns an Array containing the parameters of the distribution.
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It is used to print out the distribution and for fitting."
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^ { meanVector . covarianceMatrix }
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]
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{ #category : #information }
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PMMultivariateNormalDistribution >> power [
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"Number of dimensions of a multivariate normal distribution"
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^ meanVector size
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]
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{ #category : #information }
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PMMultivariateNormalDistribution >> random [
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"Answer a vector of random numbers distributed accroding to the receiver."
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| standardNormalRandom upperTriangular |
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standardNormalRandom := (1 to: self power) asPMVector
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collect: [ :each | PMNormalDistribution random ].
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upperTriangular := covarianceMatrix choleskyDecomposition.
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^ upperTriangular transpose * standardNormalRandom + meanVector
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]
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{ #category : #information }
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PMMultivariateNormalDistribution >> skewness [
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"Skewness is a measure of the asymmetry of the probability distribution of a real-valued random variable about its mean. Not defined for a multivariate normal distribution"
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self shouldNotImplement
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]
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{ #category : #information }
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PMMultivariateNormalDistribution >> value: aVector [
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"Answers the probability that a random variable distributed according to the receiver gives a value between aVector and aVector + espilon (infinitesimal interval)."
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^ (-1/2 * (aVector - meanVector) * covarianceMatrix inverse * (aVector - meanVector)) exp / (((2 * Float pi) raisedTo: self power) * covarianceMatrix determinant) sqrt
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]

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