Today we cut another release of our little Java mathematics library. Hipparchus is based on a fork of Apache Commons Math.

The 1.3 release includes some nice new features - most notably a redesigned Kalman filter implementation capable of handling nonlinear processes, along with quite a few additional enhancements and bug fixes.

The 1.3 release includes some nice new features - most notably a redesigned Kalman filter implementation capable of handling nonlinear processes, along with quite a few additional enhancements and bug fixes.

- Support was added for complex eigenvalue decomposition.
- A solver for continuous time algebraic Riccati equations was added.
- Secondary equations can now update the derivatives of the primary equation in ODE.
- A matrix decomposer was added to allow configuration of decomposition thresholds independently of the matrix.
- FastMath was extended to cover the new Java 9 methods so it can still serve as a drop-in replacement for java.lang.Math.

I had fun fixing some bugs in the stat package and reviewing the Kalman filter design and implementation. One of the bug fixes, for the Mann-Whitney test implementation, included implementation of exact computation of the sampling distribution of the Mann-Whitney U statistic. The algorithm for this is nice and simple, but it does not handle the case where there are ties in the data. I have started working on generalizing the algorithm (to some extent, the definition, actually) to support this. Comments, patches welcome!

The release is available on the Hipparchus download page. The release jars are available from maven central with these coordinates:

<dependency> <groupId>org.hipparchus</groupId> <artifactId>hipparchus-aggregator</artifactId> <version>1.3</version> <type>pom</type> </dependency>