MathNet.Numerics.FSharp.Sample 2.6.0

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dotnet add package MathNet.Numerics.FSharp.Sample --version 2.6.0

NuGet\Install-Package MathNet.Numerics.FSharp.Sample -Version 2.6.0

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.Sample" Version="2.6.0" />

For projects that support PackageReference, copy this XML node into the project file to reference the package.

paket add MathNet.Numerics.FSharp.Sample --version 2.6.0

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#r "nuget: MathNet.Numerics.FSharp.Sample, 2.6.0"

#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.Sample as a Cake Addin
#addin nuget:?package=MathNet.Numerics.FSharp.Sample&version=2.6.0

// Install MathNet.Numerics.FSharp.Sample as a Cake Tool
#tool nuget:?package=MathNet.Numerics.FSharp.Sample&version=2.6.0

The NuGet Team does not provide support for this client. Please contact its maintainers for support.

This package contains samples that demonstrate the use of the F# Modules for the Math.NET Numerics library. 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. Numerics is the result of merging dnAnalytics with Math.NET Iridium and is intended to replace both.

There are no supported framework assets in this package.

Learn more about Target Frameworks and .NET Standard.

- MathNet.Numerics.FSharp (>= 2.6.0)

NuGet packages

This package is not used by any NuGet packages.

GitHub repositories

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Version	Downloads	Last updated

### New: Linear Curve Fitting

- Linear least-squares fitting (regression) to lines, polynomials and linear combinations of arbitrary functions.
- Multi-dimensional fitting.
- Also works well in F# with the F# extensions.

### New: Root Finding

- Brent's method.
- Bisection method.
- Broyden's method, for multi-dimensional functions.
- Newton-Raphson method.
- Robust Newton-Raphson variant that tries to recover automatically in cases where it would fail or converge too slowly. This modification makes it more robust e.g. in the presence of singularities and less sensitive to the search range/interval.
- All algorithms support a TryFind-pattern which returns success instead of throwing an exception.
- Special case for quadratic functions, in the future to be extended e.g. to polynomials.
- Basic bracketing algorithm
- Also works well in F# with the F# extensions.

### Linear Algebra

- Native eigenvalue decomposition (EVD) support with our MKL packages
- Add missing scalar-vector operations (s-v, s/v, s%v)
- Support for new F# 3.1 row/column slicing syntax on matrices
- Matrices learned proper OfColumn/RowVectors, analog also in F#.
- Documentation Fixes
- BUG: Fixed exception text message when creating a matrix from enumerables (rows vs columns)
- We're phasing out MathNet.Numerics.IO that used to be included in the main package for matrix file I/O for text and Matlab formats. Use the new .Data.Text and .Data.Matlab packages instead.

### Statistics & Distributions

- Spearman Rank Correlation Coefficient
- Covariance function, in Array-, Streaming- and common Statistics.
- Categorical: distribution more consistent, no longer requires normalized pdf/cdf parameters
- Categorical: inverse CDF function
- BUG: Fixed static sampling methods of the `Stable` distribution.

### Misc

- BUG: Fixed a bug in the Gamma Regularized special function where in some cases with large values it returned 1 instead of 0 and vice versa.
- The F# extensions now have a strong name in (and only in) the signed package as well (previously had not been signed).
- Evaluate.Polynomial with new overload which is easier to use.
- Fixed a couple badly designed unit tests that failed on Mono.
- Repository now Vagrant-ready for easy testing against recent Mono on Debian.