Release Notes

For a detailed overview of what’s new in version 9 of Numerics.NET, see the dedicated page What’s New in Version 9.0.

This page lists the improvements since the original release of version 9.

Version 9.0.4

November 2024

  • New ChiDistribution class to represent the chi distribution and compute probabilities and quantiles.
  • New HalleySolver class to solve equations using Halley’s method, a third-order root-finding algorithm.
  • New Span based API’s: polynomial interpolation; mean, standard deviation, skewness and kurtosis estimates.
  • New extension methods for sampling without replacement.
  • New left and right tail probabilities for Parameter objects.
  • Fixed a problem with scaling the rows of sparse matrices.
  • Fixed a problem when aligning vectors with different indexes with identical values.

Version 9.0.3

November 2024

  • Support for .NET 9.0 and C# 13 features, including Span-based params lists and collection expressions for vectors and matrices.
  • New accumulator and aggregator for the Sum of Absolute Differences (SAD) of two sequences.
  • Many new tensor operators, taking advantage of new .NET 9.0 functionality.
  • Performance optimizations in the tensor library for ternary operators.

Version 9.0.2

October 2024

  • New VandermondeMatrix<T> class to represent Vandermonde matrices and solve Vandermode systems of equations efficiently.
  • New FiniteDifferenceMethod class to represent finite difference methods for approximating derivatives of functions.
  • Improvements to the Derivative method to support higher-order derivatives, higher order methods, and more.
  • Fixed an issue where the PartialLeastSquares class would not compute the predicted values correctly under some conditions.
  • Fixed a regression in the Pricipal Component Analysis class.
  • Several performance improvements and minor bug fixes.

Version 9.0.1

September 2024

  • The performance of BigInteger has been improved across the board. The difference is particularly noticeable for small numbers. By extension, BigRational and BigFloat benefit as well.
  • The scaling and standardization of features for Pricipal Component Analysis has been enhanced. Centering of variables can be disabled, and a new scaling option has bee added that ensures that the maximum absolute value of a variable is 1.
  • Improvements in the calculation of the nearest correlation matrix. The method is more reliable and now has the option to specify a minimum value for the eigenvalues of the resulting matrix.