MathNet.Numerics.FSharp 3.16.0

Prefix Reserved
There is a newer version of this package available.
See the version list below for details.
dotnet add package MathNet.Numerics.FSharp --version 3.16.0                
NuGet\Install-Package MathNet.Numerics.FSharp -Version 3.16.0                
This command is intended to be used within the Package Manager Console in Visual Studio, as it uses the NuGet module's version of Install-Package.
<PackageReference Include="MathNet.Numerics.FSharp" Version="3.16.0" />                
For projects that support PackageReference, copy this XML node into the project file to reference the package.
paket add MathNet.Numerics.FSharp --version 3.16.0                
#r "nuget: MathNet.Numerics.FSharp, 3.16.0"                
#r directive can be used in F# Interactive and Polyglot Notebooks. Copy this into the interactive tool or source code of the script to reference the package.
// Install MathNet.Numerics.FSharp as a Cake Addin
#addin nuget:?package=MathNet.Numerics.FSharp&version=3.16.0

// Install MathNet.Numerics.FSharp as a Cake Tool
#tool nuget:?package=MathNet.Numerics.FSharp&version=3.16.0                

Math.NET Numerics is the numerical foundation of the Math.NET project, aiming to provide methods and algorithms for numerical computations in science, engineering and every day use. Supports F# 3.0 on .Net 4.0, .Net 3.5 and Mono on Windows, Linux and Mac; Silverlight 5 and Windows 8 with PCL portable profile 47; Android/iOS with Xamarin.

Product Compatible and additional computed target framework versions.
.NET Framework net35 is compatible.  net40 is compatible.  net403 was computed.  net45 was computed.  net451 was computed.  net452 was computed.  net46 was computed.  net461 was computed.  net462 was computed.  net463 was computed.  net47 was computed.  net471 was computed.  net472 was computed.  net48 was computed.  net481 was computed. 
Compatible target framework(s)
Included target framework(s) (in package)
Learn more about Target Frameworks and .NET Standard.

NuGet packages (36)

Showing the top 5 NuGet packages that depend on MathNet.Numerics.FSharp:

Package Downloads
MathNet.Symbolics

Math.NET Symbolics is a basic open source computer algebra library for .Net and Mono. Written in F# but works well in C# as well. Supports .Net Framework 4.5 or higher and .Net Standard 2.0 or higher, on Windows, Linux and Mac.

FsLab

FsLab is a combination package that supports doing data science with F#. FsLab includes literate scripting converted to HTML and PDF, and by default references Deedle (a data frame library), FSharp.Data (for data access) and XPlot (for visualization). You can optionally add any other nuget packages.

OPTANO.Modeling

The OPTANO Modeling library allows you to use C# as a Modeling language for mathematical optimization (mixed integer programming (MIP) and linear programming (LP)). It has a lightweight footprint and connects to several solvers.

Deedle.Math

Deedle implements an efficient and robust frame and series data structures for manipulating with structured data. It supports handling of missing values, aggregations, grouping, joining, statistical functions and more. For frames and series with ordered indices (such as time series), automatic alignment is also available. This package installs the core Deedle package, Deedle.Math extension and Mathnet.Numerics to extend mathematic functions on Deedle Frames and Series.

Microsoft.Quantum.Research.Simulation

Quantum research libraries for quantum simulation (non-commercial).

GitHub repositories (3)

Showing the top 3 popular GitHub repositories that depend on MathNet.Numerics.FSharp:

Repository Stars
StockSharp/StockSharp
Algorithmic trading and quantitative trading open source platform to develop trading robots (stock markets, forex, crypto, bitcoins, and options).
mathnet/mathnet-numerics
Math.NET Numerics
NethermindEth/nethermind
A robust execution client for Ethereum node operators.
Version Downloads Last updated
6.0.0-beta2 112 3/2/2025
6.0.0-beta1 24,262 12/17/2023
5.0.0 939,332 4/3/2022
5.0.0-beta02 217 4/3/2022
5.0.0-beta01 19,251 3/6/2022
5.0.0-alpha16 217 2/27/2022
5.0.0-alpha15 219 2/27/2022
5.0.0-alpha14 207 2/27/2022
5.0.0-alpha13 200 2/27/2022
5.0.0-alpha12 207 2/27/2022
5.0.0-alpha11 200 2/27/2022
5.0.0-alpha10 217 2/19/2022
5.0.0-alpha09 206 2/13/2022
5.0.0-alpha08 280 12/23/2021
5.0.0-alpha07 214 12/19/2021
5.0.0-alpha06 220 12/19/2021
5.0.0-alpha05 235 12/19/2021
5.0.0-alpha04 235 12/19/2021
5.0.0-alpha03 248 12/5/2021
5.0.0-alpha02 432 7/11/2021
5.0.0-alpha01 367 6/27/2021
4.15.0 548,074 1/7/2021
4.14.0 1,713 1/1/2021
4.13.0 625 12/30/2020
4.12.0 37,264 8/2/2020
4.11.0 129,071 5/24/2020
4.10.0 702 5/24/2020
4.9.1 20,637 4/12/2020
4.9.0 75,043 10/13/2019
4.8.1 195,812 6/11/2019
4.8.0 2,466 6/2/2019
4.8.0-beta02 537 5/30/2019
4.8.0-beta01 588 4/28/2019
4.7.0 136,068 11/11/2018
4.6.0 3,690 10/19/2018
4.5.1 33,700 5/22/2018
4.5.0 1,350 5/22/2018
4.4.1 1,795 5/6/2018
4.4.0 13,902 2/25/2018
4.3.0 1,317 2/24/2018
4.2.0 2,630 2/21/2018
4.1.0 2,236 2/19/2018
4.0.0 6,023 2/11/2018
4.0.0-beta07 1,019 2/10/2018
4.0.0-beta06 1,043 2/3/2018
4.0.0-beta05 1,046 1/22/2018
4.0.0-beta04 1,033 1/13/2018
4.0.0-beta03 1,005 1/9/2018
4.0.0-beta02 1,132 1/7/2018
4.0.0-beta01 986 1/7/2018
4.0.0-alpha04 967 1/5/2018
4.0.0-alpha03 966 12/26/2017
4.0.0-alpha02 948 11/30/2017
4.0.0-alpha01 943 11/26/2017
3.20.2 12,773 1/22/2018
3.20.1 1,553 1/13/2018
3.20.0 52,302 7/15/2017
3.20.0-beta01 965 5/31/2017
3.19.0 8,085 4/29/2017
3.18.0 15,238 4/9/2017
3.17.0 10,876 1/15/2017
3.16.0 1,848 1/3/2017
3.15.0 1,427 12/27/2016
3.14.0-beta03 996 11/20/2016
3.14.0-beta02 940 11/15/2016
3.14.0-beta01 978 10/30/2016
3.13.1 72,474 9/6/2016
3.13.0 1,675 8/18/2016
3.12.0 8,416 7/3/2016
3.11.1 14,672 4/24/2016
3.11.0 8,605 2/13/2016
3.10.0 11,248 12/30/2015
3.9.0 4,272 11/25/2015
3.8.0 52,408 9/26/2015
3.7.1 4,235 9/21/2015
3.7.0 17,038 5/9/2015
3.6.0 11,982 3/22/2015
3.5.0 7,621 1/10/2015
3.4.0 2,050 1/4/2015
3.3.0 3,126 11/26/2014
3.3.0-beta2 1,088 10/25/2014
3.3.0-beta1 1,126 9/28/2014
3.2.3 25,718 9/6/2014
3.2.2 1,446 9/5/2014
3.2.1 1,872 8/5/2014
3.2.0 1,419 8/5/2014
3.1.0 4,135 7/20/2014
3.0.2 1,884 6/26/2014
3.0.1 1,496 6/24/2014
3.0.0 10,925 6/21/2014
3.0.0-beta05 1,176 6/20/2014
3.0.0-beta04 1,133 6/15/2014
3.0.0-beta03 1,139 6/5/2014
3.0.0-beta02 1,112 5/29/2014
3.0.0-beta01 3,945 4/14/2014
3.0.0-alpha9 1,201 3/29/2014
3.0.0-alpha8 1,168 2/26/2014
3.0.0-alpha7 7,684 12/30/2013
3.0.0-alpha6 1,297 12/2/2013
3.0.0-alpha5 3,911 10/2/2013
3.0.0-alpha4 1,218 9/22/2013
3.0.0-alpha1 1,147 9/1/2013
2.6.0 14,044 7/26/2013
2.5.0 2,175 4/14/2013
2.4.0 1,859 2/3/2013
2.3.0 1,956 11/25/2012
2.2.1 1,877 8/29/2012
2.2.0 1,655 8/27/2012
2.1.2 6,647 10/9/2011
2.1.1 1,857 10/3/2011
2.1.0.19 2,441 10/3/2011

Root Finding: improve accuracy handling ~Konstantin Tretyakov
Regression: GoodnessOfFit StandardError ~David Falkner