SigmaSwiftStatistics

To use the library in your Swift source code, add the following import statement. If you are using the file setup method instead of a package manager, you may not need this.

import SigmaSwiftStatistics

To install SigmaSwiftStatistics using Swift Package Manager in Xcode 11 or later:

1. In Xcode, select File > Packages > Add Package Dependency....
2. Enter the following URL: https://github.com/evgenyneu/SigmaSwiftStatistics.git

You can integrate the SigmaSwiftStatistics library into your project using one of the following four methods:

1. Add Source (iOS 7+): Manually add the SigmaDistrib.swift file to your project.
2. Carthage (iOS 8+): Add the dependency to your Cartfile and run carthage update.
3. CocoaPods (iOS 8+): Add the pod to your Podfile and run pod install.
4. Swift Package Manager (Xcode 11+): Add the repository URL via the Xcode Package Manager interface.

# Carthage
github "evgenyneu/SigmaSwiftStatistics" ~> 9.0

# CocoaPods
use_frameworks!
target 'Your target name' do
  pod 'SigmaSwiftStatistics', '~> 9.0'
end

Calculates the Pearson product-moment correlation coefficient between two variables x and y.

Note:

• Returns nil if arrays have different lengths or are empty.
• Equivalent to CORREL in Excel/Google Sheets.

let x = [1, 2, 3.5, 3.7, 8, 12]
let y = [0.5, 1, 2.1, 3.4, 3.4, 4]
Sigma.pearson(x: x, y: y)

Computes the variance of a dataset.

Variance of a Population

• Returns nil if the array is empty.
• Equivalent to VAR.P or VARPA in Excel.

Sigma.variancePopulation([1, 12, 19.5, -5, 3, 8])

Variance of a Sample

• Returns nil if the array is empty or contains a single value.
• Equivalent to VAR or VAR.S in Excel.

Sigma.varianceSample([1, 12, 19.5, -5, 3, 8])

Returns the skewness of the dataset.

Skewness A

• Returns nil if the dataset has less than 3 values or if all values are identical.
• Equivalent to SKEW in Excel/Google Sheets.

Sigma.skewnessA([4, 2.1, 8, 21, 1])

Skewness B

• Returns nil if the dataset has less than 3 values or if all values are identical.
• Equivalent to SKEW.P in Excel and the "moments" R package.

Sigma.skewnessB([4, 2.1, 8, 21, 1])

Returns a dictionary where keys are the unique numbers from the input array and values are their respective frequencies.

Sigma.frequencies([1, 2, 3, 4, 5, 4, 4, 3, 5])
// Result: [2:1, 3:2, 4:3, 5:2, 1:1]

Calculates the percentile value for a given dataset.

Note:

• Returns nil if the array is empty or if percentile is not in the range [0, 1].
• Uses the 7th sample quantile method from Hyndman and Fan (1996).

Sigma.percentile([35, 20, 50, 40, 15], percentile: 0.4)

Returns the kurtosis of a series of numbers.

Kurtosis A

• Returns nil if the dataset has less than 4 values or if all values are identical.
• Equivalent to KURT in Excel/Google Sheets.

Sigma.kurtosisA([2, 1, 3, 4.1, 19, 1.5])

Kurtosis B

• Returns nil if the dataset has less than 2 values or if all values are identical.
• Equivalent to Wolfram Alpha and the "moments" R package.

Sigma.kurtosisB([2, 1, 3, 4.1, 19, 1.5])

Simple utility functions for array manipulation.

• Sigma.sum(array): Computes the sum of values.
• Sigma.max(array): Returns the maximum value (returns nil if empty).
• Sigma.min(array): Returns the minimum value (returns nil if empty).
• Sigma.uniqueValues(array): Returns an unsorted array of unique values without duplicates.

Sigma.sum([1, 3, 8])
Sigma.max([1, 8, 3])
Sigma.min([7, 2, 3])
Sigma.uniqueValues([2, 1, 3, 4, 5, 4, 3, 5])