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Updated Release: Math.NET Numerics v2.5.0 (Apr 14, 2013)

cdrnet — Sun, 14 Apr 2013 18:59:20 GMT

Potentially Breaking Changes:

Despite semver this release contains two changes that may break code but without triggering a major version number change. The changes fix semantic bugs and a major usability issue without changing the formal API itself. Most users are not expected to be affected negatively. Nevertheless, this is an exceptional case and we try hard to avoid such changes in the future.

Statistics: Empty statistics now return NaN instead of either 0 or throwing an exception. This may break code in case you relied upon the previous unusual and inconsistent behavior.

Linear Algebra: More reasonable ToString behavior for matrices and vectors. This may break code if you relied upon ToString to export your full data to text form intended to be parsed again later. Note that the classes in the MathNet.Numerics.IO library are more appropriate for storing and loading data.

Statistics:

More consistent behavior for empty and single-element data sets: Min, Max, Mean, Variance, Standard Deviation etc. no longer throw exceptions if the data set is empty but instead return NaN. Variance and Standard Deviation will also return NaN if the set contains only a single entry. Population Variance and Population Standard Deviation will return 0 in this case.
Reworked order statistics (Quantile, Quartile, Percentile, IQR, Fivenum, etc.), now much easier to use and supporting compatibility with all 9 R-types, Excel and Mathematica. The obsolete Percentile class now leverages the new order statistics, fixing a range check bug as side effect.
New Hybrid Monte Carlo sampler for multivariate distributions.
New financial statistics: absolute risk and return measures.
Explicit statistics for sorted arrays, unsorted arrays and sequences/streams. Faster algorithms on sorted data, also avoids multiple enumerations.
Some statistics like Quantile or empirical inverse CDF can optionally return a parametric function when multiple evaluations are needed, like for plotting.

Linear Algebra:

More reasonable ToString behavior for matrices and vectors: `ToString` methods no longer render the whole structure to a string for large data, among others because they used to wreak havoc in debugging and interactive scenarios like F# FSI. Instead, ToString now only renders an excerpt of the data, together with a line about dimension, type and in case of sparse data a sparseness indicator. The intention is to give a good idea about the data in a visually useful way. How much data is shown can be adjusted in the Control class. See also ToTypeString and ToVector/MatrixString.
Performance: reworked and tuned common parallelization. Some operations are up to 3 magnitudes faster in some extreme cases. Replaced copy loops with native routines. More algorithms are storage-aware (and should thus perform better especially on sparse data).
Fixed range checks in the Thin-QR decomposition.
Fixed bug in Gram Schmidt for solving tall matrices.
Vectors now implement the BCL IList interfaces (fixed-length) for better integration with existing .Net code.
Matrix/Vector parsing has been updated to be able to parse the new visual format as well (see ToMatrixString).
DebuggerDisplay attributes for matrices and vectors.
Map/IndexedMap combinators with storage-aware and partially parallelized implementations for both dense and sparse data.
Reworked Matrix/Vector construction from arrays, enumerables, indexed enumerables, nested enumerables or by providing an init function/lambda. Non-obsolete constructors now always use the raw data array directly without copying, while static functions always return a matrix/vector independent of the provided data source.
F#: Improved extensions for matrix and vector construction: create, zeroCreate, randomCreate, init, ofArray2, ofRows/ofRowsList, ofColumns/ofColumnsList, ofSeqi/Listi (indexed). Storage-aware for performance.
F#: Updated map/mapi and other combinators to leverage core implementation, added -nz variants where zero-values may be skipped (relevant mostly for sparse matrices).
F#: Idiomatic slice setters for sub-matrices and sub-vectors
F#: More examples for matrix/vector creation and linear regression in the F# Sample-package.

Misc:

Control: Simpler usage with new static ConfigureAuto and ConfigureSingleThread methods. Resolved misleading configuration logic and naming around disabling parallelization.
Control: New settings for linear algebra ToString behavior.
Fixed range check in the Xor-shift pseudo-RNG.
Parallelization: Reworked our common logic to avoid expensive lambda calls in inner loops. Tunable.
F#: Examples (and thus the NuGet Sample package) are now F# scripts prepared for experimenting interactively in FSI, instead of normal F# files. Tries to get the assembly references right for most users, both within the Math.NET Numerics solution and the NuGet package.
Various minor improvements on consistency, performance, tests, xml docs, obsolete attributes, redundant code, argument checks, resources, cleanup, nuget, etc.

Also available as NuGet packages:
PM> Install-Package MathNet.Numerics
PM> Install-Package MathNet.Numerics.FSharp

Code samples:
PM> Install-Package MathNet.Numerics.Sample
PM> Install-Package MathNet.Numerics.FSharp.Sample

If you absolutely require a signed library with a strong name:
PM> Install-Package MathNet.Numerics.Signed

Released: Math.NET Numerics v2.5.0 (Apr 14, 2013)

Sun, 14 Apr 2013 18:59:20 GMT

Statistics: Empty statistics now return NaN instead of either 0 or throwing an exception. This may break code in case you relied upon the previous unusual and inconsistent behavior.

Linear Algebra: More reasonable ToString behavior for matrices and vectors. This may break code if you relied upon ToString to export your full data to text form intended to be parsed again later. Note that the classes in the MathNet.Numerics.IO library are more appropriate for storing and loading data.

Statistics:

More consistent behavior for empty and single-element data sets: Min, Max, Mean, Variance, Standard Deviation etc. no longer throw exceptions if the data set is empty but instead return NaN. Variance and Standard Deviation will also return NaN if the set contains only a single entry. Population Variance and Population Standard Deviation will return 0 in this case.
Reworked order statistics (Quantile, Quartile, Percentile, IQR, Fivenum, etc.), now much easier to use and supporting compatibility with all 9 R-types, Excel and Mathematica. The obsolete Percentile class now leverages the new order statistics, fixing a range check bug as side effect.
New Hybrid Monte Carlo sampler for multivariate distributions.
New financial statistics: absolute risk and return measures.
Explicit statistics for sorted arrays, unsorted arrays and sequences/streams. Faster algorithms on sorted data, also avoids multiple enumerations.
Some statistics like Quantile or empirical inverse CDF can optionally return a parametric function when multiple evaluations are needed, like for plotting.

Linear Algebra:

More reasonable ToString behavior for matrices and vectors: `ToString` methods no longer render the whole structure to a string for large data, among others because they used to wreak havoc in debugging and interactive scenarios like F# FSI. Instead, ToString now only renders an excerpt of the data, together with a line about dimension, type and in case of sparse data a sparseness indicator. The intention is to give a good idea about the data in a visually useful way. How much data is shown can be adjusted in the Control class. See also ToTypeString and ToVector/MatrixString.
Performance: reworked and tuned common parallelization. Some operations are up to 3 magnitudes faster in some extreme cases. Replaced copy loops with native routines. More algorithms are storage-aware (and should thus perform better especially on sparse data).
Fixed range checks in the Thin-QR decomposition.
Fixed bug in Gram Schmidt for solving tall matrices.
Vectors now implement the BCL IList interfaces (fixed-length) for better integration with existing .Net code.
Matrix/Vector parsing has been updated to be able to parse the new visual format as well (see ToMatrixString).
DebuggerDisplay attributes for matrices and vectors.
Map/IndexedMap combinators with storage-aware and partially parallelized implementations for both dense and sparse data.
Reworked Matrix/Vector construction from arrays, enumerables, indexed enumerables, nested enumerables or by providing an init function/lambda. Non-obsolete constructors now always use the raw data array directly without copying, while static functions always return a matrix/vector independent of the provided data source.
F#: Improved extensions for matrix and vector construction: create, zeroCreate, randomCreate, init, ofArray2, ofRows/ofRowsList, ofColumns/ofColumnsList, ofSeqi/Listi (indexed). Storage-aware for performance.
F#: Updated map/mapi and other combinators to leverage core implementation, added -nz variants where zero-values may be skipped (relevant mostly for sparse matrices).
F#: Idiomatic slice setters for sub-matrices and sub-vectors
F#: More examples for matrix/vector creation and linear regression in the F# Sample-package.

Misc:

Control: Simpler usage with new static ConfigureAuto and ConfigureSingleThread methods. Resolved misleading configuration logic and naming around disabling parallelization.
Control: New settings for linear algebra ToString behavior.
Fixed range check in the Xor-shift pseudo-RNG.
Parallelization: Reworked our common logic to avoid expensive lambda calls in inner loops. Tunable.
F#: Examples (and thus the NuGet Sample package) are now F# scripts prepared for experimenting interactively in FSI, instead of normal F# files. Tries to get the assembly references right for most users, both within the Math.NET Numerics solution and the NuGet package.
Various minor improvements on consistency, performance, tests, xml docs, obsolete attributes, redundant code, argument checks, resources, cleanup, nuget, etc.

Created Release: Math.NET Numerics v2.5.0 (Apr 14, 2013)

cdrnet — Sun, 14 Apr 2013 18:19:48 GMT

Statistics: Empty statistics now return NaN instead of either 0 or throwing an exception. This may break code in case you relied upon the previous unusual and inconsistent behavior.

Linear Algebra: More reasonable ToString behavior for matrices and vectors. This may break code if you relied upon ToString to export your full data to text form intended to be parsed again later. Note that the classes in the MathNet.Numerics.IO library are more appropriate for storing and loading data.

Statistics:

More consistent behavior for empty and single-element data sets: Min, Max, Mean, Variance, Standard Deviation etc. no longer throw exceptions if the data set is empty but instead return NaN. Variance and Standard Deviation will also return NaN if the set contains only a single entry. Population Variance and Population Standard Deviation will return 0 in this case.
Reworked order statistics (Quantile, Quartile, Percentile, IQR, Fivenum, etc.), now much easier to use and supporting compatibility with all 9 R-types, Excel and Mathematica. The obsolete Percentile class now leverages the new order statistics, fixing a range check bug as side effect.
New Hybrid Monte Carlo sampler for multivariate distributions.
New financial statistics: absolute risk and return measures.
Explicit statistics for sorted arrays, unsorted arrays and sequences/streams. Faster algorithms on sorted data, also avoids multiple enumerations.
Some statistics like Quantile or empirical inverse CDF can optionally return a parametric function when multiple evaluations are needed, like for plotting.

Linear Algebra:

More reasonable ToString behavior for matrices and vectors: `ToString` methods no longer render the whole structure to a string for large data, among others because they used to wreak havoc in debugging and interactive scenarios like F# FSI. Instead, ToString now only renders an excerpt of the data, together with a line about dimension, type and in case of sparse data a sparseness indicator. The intention is to give a good idea about the data in a visually useful way. How much data is shown can be adjusted in the Control class. See also ToTypeString and ToVector/MatrixString.
Performance: reworked and tuned common parallelization. Some operations are up to 3 magnitudes faster in some extreme cases. Replaced copy loops with native routines. More algorithms are storage-aware (and should thus perform better especially on sparse data).
Fixed range checks in the Thin-QR decomposition.
Fixed bug in Gram Schmidt for solving tall matrices.
Vectors now implement the BCL IList interfaces (fixed-length) for better integration with existing .Net code.
Matrix/Vector parsing has been updated to be able to parse the new visual format as well (see ToMatrixString).
DebuggerDisplay attributes for matrices and vectors.
Map/IndexedMap combinators with storage-aware and partially parallelized implementations for both dense and sparse data.
Reworked Matrix/Vector construction from arrays, enumerables, indexed enumerables, nested enumerables or by providing an init function/lambda. Non-obsolete constructors now always use the raw data array directly without copying, while static functions always return a matrix/vector independent of the provided data source.
F#: Improved extensions for matrix and vector construction: create, zeroCreate, randomCreate, init, ofArray2, ofRows/ofRowsList, ofColumns/ofSolumnsList, ofSeqi/Listi (indexed). Storage-aware for performance.
F#: Updated map/mapi and other combinators to leverage core implementation, added -nz variants where zero-values may be skipped (relevant mostly for sparse matrices).
F#: Idiomatic slice setters for sub-matrices and sub-vectors
F#: More examples for matrix/vector creation and linear regression in the F# Sample-package.

Misc:

Control: Simpler usage with new static ConfigureAuto and ConfigureSingleThread methods. Resolved misleading configuration logic and naming around disabling parallelization.
Control: New settings for linear algebra ToString behavior.
Fixed range check in the Xor-shift pseudo-RNG.
Parallelization: Reworked our common logic to avoid expensive lambda calls in inner loops. Tunable.
F#: Examples (and thus the NuGet Sample package) are now F# scripts prepared for experimenting interactively in FSI, instead of normal F# files. Tries to get the assembly references right for most users, both within the Math.NET Numerics solution and the NuGet package.
Various minor improvements on consistency, performance, tests, xml docs, obsolete attributes, redundant code, argument checks, resources, cleanup, nuget, etc.

Updated Release: Math.NET Numerics v2.4.0 (Feb 03, 2013)

cdrnet — Sun, 03 Feb 2013 22:02:39 GMT

Drops the dependency on the zlib library. We thus no longer have any dependencies on other packages.
Adds Modified Bessel & Struve special functions
Fixes a bug in our iterative kurtosis statistics formula

Linear Algebra:

Performance work, this time mostly around accessing matrix rows/columns as vectors. Opting out from targeted patching in our matrix and vector indexers to allow inlining.
Fixes an issue around Thin-QR solve
Simplifications around using native linear algebra providers (see Math.NET Numerics With Native Linear Algebra)

F#:

Adds the BigRational module from the F# PowerPack, now to be maintained here instead.
Better support for our Complex types (close to the F# PowerPack Complex type)

Thanks a lot for all the contributions, notably from Marcus Cuda, Gustavo Guerra, Artyom Baranovskiy, Thomas Ibel and Wayne Wu.

Also available as NuGet packages:
PM> Install-Package MathNet.Numerics
PM> Install-Package MathNet.Numerics.FSharp

If you absolutely require a signed library with a strong name:
PM> Install-Package MathNet.Numerics.Signed

Released: Math.NET Numerics v2.4.0 (Feb 03, 2013)

Sun, 03 Feb 2013 22:02:39 GMT

Drops the dependency on the zlib library. We thus no longer have any dependencies on other packages.
Adds Modified Bessel & Struve special functions
Fixes a bug in our iterative kurtosis statistics formula

Linear Algebra:

Performance work, this time mostly around accessing matrix rows/columns as vectors. Opting out from targeted patching in our matrix and vector indexers to allow inlining.
Fixes an issue around Thin-QR solve
Simplifications around using native linear algebra providers (see Math.NET Numerics With Native Linear Algebra)

F#:

Adds the BigRational module from the F# PowerPack, now to be maintained here instead.
Better support for our Complex types (close to the F# PowerPack Complex type)

Created Release: Math.NET Numerics v2.4.0 (Feb 03, 2013)

cdrnet — Sun, 03 Feb 2013 19:37:57 GMT

Drops the dependency on the zlib library. We thus no longer have any dependencies on other packages.
Adds Modified Bessel & Struve special functions
Fixes a bug in our iterative kurtosis statistics formula

Linear Algebra:

Performance work, this time mostly around accessing matrix rows/columns as vectors. Opting out from targeted patching in our matrix and vector indexers to allow inlining.
Fixes an issue around Thin-QR solve
Simplifications around using native linear algebra providers (more details to be added here later)

F#:

Adds the BigRational module from the F# PowerPack, now to be maintained here instead.
Better support for our Complex types (close to the F# PowerPack Complex type)

Released: Math.NET Numerics v2.4.0 (Feb 03, 2013)

Sun, 03 Feb 2013 19:37:57 GMT

Drops the dependency on the zlib library. We thus no longer have any dependencies on other packages.
Adds Modified Bessel & Struve special functions
Fixes a bug in our iterative kurtosis statistics formula

Linear Algebra:

Performance work, this time mostly around accessing matrix rows/columns as vectors. Opting out from targeted patching in our matrix and vector indexers to allow inlining.
Fixes an issue around Thin-QR solve
Simplifications around using native linear algebra providers (more details to be added here later)

F#:

Adds the BigRational module from the F# PowerPack, now to be maintained here instead.
Better support for our Complex types (close to the F# PowerPack Complex type)

Updated Release: Math.NET Numerics v2.3.0 (Nov 25, 2012)

cdrnet — Mon, 26 Nov 2012 10:05:27 GMT

Portable Library Build:

Adds support for WP8 (.Net 4.0 and higher, SL5, WP8 and .NET for Windows Store apps)
New: portable build also for F# extensions (.Net 4.5, SL5 and .NET for Windows Store apps)
NuGet: portable builds are now included in the main packages, no more need for special portable packages

Linear Algebra:

Continued major storage rework, in this release focusing on vectors (previous release was on matrices)
Thin QR decomposition (in addition to existing full QR)
Static CreateRandom for all dense matrix and vector types
F#: slicing support for matrices and vectors

Random and Probability Distributions:

Consistent static Sample methods for all continuous and discrete distributions (was previously missing on a few)
F#: better usability for random numbers and distributions.

Misc:

F# extensions are now using F# 3.0
Updated Intel MKL references for our native linear algebra providers
Various bug, performance and usability fixes

Also available as NuGet packages:
PM> Install-Package MathNet.Numerics
PM> Install-Package MathNet.Numerics.FSharp

Note: The portable package MathNet.Numerics.Portable has been dropped, as NuGet 2.1 properly supports portable builds in the main package.

If you absolutely require a signed library with a strong name:
PM> Install-Package MathNet.Numerics.Signed

Released: Math.NET Numerics v2.3.0 (Nov 25, 2012)

Mon, 26 Nov 2012 10:05:27 GMT

Portable Library Build:

Adds support for WP8 (.Net 4.0 and higher, SL5, WP8 and .NET for Windows Store apps)
New: portable build also for F# extensions (.Net 4.5, SL5 and .NET for Windows Store apps)
NuGet: portable builds are now included in the main packages, no more need for special portable packages

Linear Algebra:

Continued major storage rework, in this release focusing on vectors (previous release was on matrices)
Thin QR decomposition (in addition to existing full QR)
Static CreateRandom for all dense matrix and vector types
F#: slicing support for matrices and vectors

Random and Probability Distributions:

Consistent static Sample methods for all continuous and discrete distributions (was previously missing on a few)
F#: better usability for random numbers and distributions.

Misc:

F# extensions are now using F# 3.0
Updated Intel MKL references for our native linear algebra providers
Various bug, performance and usability fixes

Updated Release: Math.NET Numerics v2.3.0 (Nov 25, 2012)

cdrnet — Mon, 26 Nov 2012 00:21:36 GMT

Common:

Continued major linear algebra storage rework, in this release focusing on vectors (previous release was on matrices)
Static CreateRandom for all dense matrix and vector types
Thin QR decomposition (in additin to existing full QR)
Consistent static Sample methods for continuous and discrete distributions (was previously missing on a few)
Portable build adds support for WP8 (.Net 4.0 and higher, SL5, WP8 and .NET for Windows Store apps)
Various bug, performance and usability fixes

F# specific:

F# 3.0
Portable build available (.Net 4.5, SL5 and .NET for Windows Store apps)
Slicing support for matrices and vectors
Better usability for random numbers and distributions.

Native providers:

Updated MKL references

Released: Math.NET Numerics v2.3.0 (Nov 25, 2012)

Mon, 26 Nov 2012 00:21:36 GMT

Common:

Continued major linear algebra storage rework, in this release focusing on vectors (previous release was on matrices)
Static CreateRandom for all dense matrix and vector types
Thin QR decomposition (in additin to existing full QR)
Consistent static Sample methods for continuous and discrete distributions (was previously missing on a few)
Portable build adds support for WP8 (.Net 4.0 and higher, SL5, WP8 and .NET for Windows Store apps)
Various bug, performance and usability fixes

F# specific:

F# 3.0
Portable build available (.Net 4.5, SL5 and .NET for Windows Store apps)
Slicing support for matrices and vectors
Better usability for random numbers and distributions.

Native providers:

Updated MKL references

Updated Release: Math.NET Numerics v2.3.0 (Nov 25, 2012)

cdrnet — Mon, 26 Nov 2012 00:09:38 GMT

Common:

Continued major linear algebra storage rework, in this release focusing on vectors (previous release was on matrices)
Static CreateRandom for all dense matrix and vector types
Thin QR decomposition (in additin to existing full QR)
Consistent static Sample methods for continuous and discrete distributions (was previously missing on a few)
Portable build adds support for WP8 (.Net 4.0 and higher, SL5, WP8 and .NET for Windows Store apps)
Various bug, performance and usability fixes

F# specific:

F# 3.0
Portable build available (.Net 4.5, SL5 and .NET for Windows Store apps)
Slicing support for matrices and vectors
Better usability for random numbers and distributions. The "FSharp" module is no longer needed.

Native providers:

Updated MKL references

Updated Release: Math.NET Numerics v2.3.0 (Nov 25, 2012)

cdrnet — Sun, 25 Nov 2012 15:56:43 GMT

Common:

Continued major linear algebra storage rework, in this release focusing on vectors (previous release was on matrices)
Static CreateRandom for all dense matrix and vector types
Thin QR decomposition (in additin to existing full QR)
Consistent static Sample methods for continuous and discrete distributions (was previously missing on a few)
Portable build adds support for WP8 (.Net 4.0 and higher, SL5, WP8 and .NET for Windows Store apps)
Various bug, performance and usability fixes

F# specific:

F# 3.0
Portable build available (.Net 4.5, SL5 and .NET for Windows Store apps)
F#: slicing support for matrices and vectors
F#: new modules for random numbers and distributions. Dropped "FSharp" module.

Native providers:

Updated MKL references

Released: Math.NET Numerics v2.3.0 (Nov 25, 2012)

Sun, 25 Nov 2012 15:56:43 GMT

Common:

Continued major linear algebra storage rework, in this release focusing on vectors (previous release was on matrices)
Static CreateRandom for all dense matrix and vector types
Thin QR decomposition (in additin to existing full QR)
Consistent static Sample methods for continuous and discrete distributions (was previously missing on a few)
Portable build adds support for WP8 (.Net 4.0 and higher, SL5, WP8 and .NET for Windows Store apps)
Various bug, performance and usability fixes

F# specific:

F# 3.0
Portable build available (.Net 4.5, SL5 and .NET for Windows Store apps)
F#: slicing support for matrices and vectors
F#: new modules for random numbers and distributions. Dropped "FSharp" module.

Native providers:

Updated MKL references

Created Release: Math.NET Numerics v2.3.0 (Nov 25, 2012)

cdrnet — Sun, 25 Nov 2012 15:49:58 GMT

Common:

Continued major linear algebra storage rework, in this release focusing on vectors (previous release was on matrices)
Static CreateRandom for all dense matrix and vector types
Thin QR decomposition (in additin to existing full QR)
Consistent static Sample methods for continuous and discrete distributions (was previously missing on a few)
Portable build adds support for WP8
Various bug, performance and usability fixes

F# specific:

F# 3.0
Portable build now also for F# modules
F#: slicing support for matrices and vectors
F#: new modules for random numbers and distributions. Dropped "FSharp" module.

Native providers:

Updated MKL references

Created Release: Math.NET Numerics v2.2.1 (Aug 29, 2012)

cdrnet — Wed, 29 Aug 2012 14:17:21 GMT

Major linear algebra rework since v2.1, now available on Codeplex as well (previous versions were only available via NuGet).

Since v2.2.0:

Student-T density more robust for very large degrees of freedom
Sparse Kronecker product much more efficient (now leverages sparsity)
Direct access to raw matrix storage implementations for advanced extensibility
Now also separate package for signed core library with a strong name (we dropped strong names in v2.2.0)

Also available as NuGet packages:
PM> Install-Package MathNet.Numerics
PM> Install-Package MathNet.Numerics.FSharp

New: instead of the special Silverlight build we now provide a portable version supporting .Net 4, Silverlight 5 and .Net Core (WinRT) 4.5:
PM> Install-Package MathNet.Numerics.Portable

If you absolutely require a signed library with a strong name:
PM> Install-Package MathNet.Numerics.Signed

Released: Math.NET Numerics v2.2.1 (Aug 29, 2012)

Wed, 29 Aug 2012 14:17:21 GMT

Major linear algebra rework since v2.1, now available on Codeplex as well (previous versions were only available via NuGet).

Since v2.2.0:

Student-T density more robust for very large degrees of freedom
Sparse Kronecker product much more efficient (now leverages sparsity)
Direct access to raw matrix storage implementations for advanced extensibility
Now also separate package for signed core library with a strong name (we dropped strong names in v2.2.0)

Created Release: Math.NET Numerics v2.2.0 (Aug 27, 2012)

cdrnet — Mon, 27 Aug 2012 17:03:14 GMT

Major linear algebra rework since v2.1, now available on Codeplex as well (previous versions were only available via NuGet).

Also available as NuGet packages:
PM> Install-Package MathNet.Numerics
PM> Install-Package MathNet.Numerics.FSharp

New: instead of the special Silverlight build we now provide a portable version supporting .Net 4, Silverlight 5 and .Net Core (WinRT) 4.5:
PM> Install-Package MathNet.Numerics.Portable

Released: Math.NET Numerics v2.2.0 (Aug 27, 2012)

Mon, 27 Aug 2012 17:03:14 GMT

Updated Release: Beta 2 (Apr 17, 2011)

cuda — Sun, 17 Apr 2011 13:20:25 GMT

Second beta release.
This release includes numerous bug fixes, native wrappers for ACML and MKL (do to licensing restrictions, users will have to build the providers themselves), and several breaking API changes/improvements.

This is the final beta release and we are now working on improving performance, unit tests, and documentation.