What's New in Version 7.0

.NET Core and .NET Standard support

  • Support for .NET Core 1.1 and 2.1.
  • Support for .NET Standard 1.3 and 2.0.
  • Support for .NET Framework 3.5, 4.0, 4.72 and later.
  • All packages are available on the Nuget Gallery.

Linear algebra

Major enhancements

  • Broadcasting vectors in matrix operations.
  • Enable Conditional Numerical Reproducibility option for native libraries.
  • Upgraded native libraries to Intel® Math Kernel Library version 2019 Update 0.
  • Upgraded managed linear algebra library to LAPACK 3.7.0.
  • Improved range and accuracy of matrix exponential.
  • Vector Map methods that include index as delegate argument.

New matrix decompositions

Performance improvements

  • Improve performance for level 2 managed sparse BLAS.
  • Improve performance for various vector operations.
  • The threshold for parallel execution of vector maps can now be configured.


General improvements

  • The generic Operations<T> class has been optimized to eliminate nearly all overhead for the most frequently used operations on the most common argument types.
  • ParallelOptions is now exposed for all algorithms to enable cancellation and other scenarios.
  • Combinatorial iterators to enumerate all combinations, permutations, and Cartesian products of sets of items.
  • New overloads for numerical integration methods that take Interval objects to specify bounds.
  • Inverse hyperbolic functions for decimal and quad precision numbers.


  • The NonlinearProgram class has a new constructor that accepts variable names.
  • Symbolic constraints that are linear in the variables are now recognized as such.
  • The Nonlinear Program solver can now recover when it encounters an infeasible subproblem.
  • Up to 30% improvement in the performance of the Linear Program solver
  • Limited Memory BFGS Optimizer.
  • LeastSquaresOptimizer base class for nonlinear least squares algorithms.
  • Trust Region Reflexive algorithm for nonlinear least squares.
  • Trust Region Reflexive algorithm option in nonlinear curve fitting.
  • Improved documentation for nonlinear least squares algorithms.

Special functions

Statistics and data analysis

Data access library

  • Data Access Library providing a unified API for reading and writing data frames, matrices, and vectors.
  • Reading and writing R’s .rda/.rdata and .rds files.
  • JSON serialization.
  • Other supported formats include: delimited text (CSV, TSV…), fixed-width text, Matrix Market, Matlab®, stata®

Statistical models

Hypothesis tests

Data analysis

Want to go further back? See what was new in version 6.0.