Tasks: Done And To Do

This page aims to be a handy reference not only of the work done but also of work pending for the next planned release. Users who want new features should submit patches to this page in the unclassified section of this document. Developers who want to lend a hand can grab tasks from this page. Everyone can see the progress which is being made.

The following is a list of items still TODO for Math. Contributions are welcome!

  • Fill Me In! With A High Priority Task
  • Fill Me In With A Medium Priority Task
  • Fill Me In With A Low Priority Task
Tasklist is based on an email from Phil Steitz on May 21, 2003
  • Add quantiles (1,5,10,25,50,75,90,95,99) to all Univaraite implementations and bootstrap confidence intervals to StoredUnivariate implementations.
  • Add higher order moments to StoredUnivariate (UnivariateImpl if possible).
  • t-test statistic needs to be added and we should probably add the capability of actually performing t- and chi-square tests at fixed significance levels (.1, .05, .01, .001).
  • numerical approximation of the t- and chi-square distributions to enable user-supplied significance levels.
  • The RealMatrixImpl class is missing some key method implementations. The critical thing is inversion. We need to implement a numerically sound inversion algorithm. This will enable solve() and also support general linear regression.
  • ComplexNumber interface and implementation. The only tricky thing here is making division numerically sound and what extended value topology to adopt.
  • Bivariate Regression, corellation. This could be done with simple formulas manipulating arrays and this is probably what we should aim for in an initial release. Down the road, we should use the RealMatrixImpl solve() to support general linear regression.
  • Binomial coefficients An "exact" implementation that is limited to what can be stored in a long exists. This should be extended to use BigIntegers and potentially to support logarithmic representations.
  • Newton's method for finding roots
  • Exponential growth and decay
  • Polynomial Interpolation (curve fitting)
  • Sampling from Collections
  • Addition of a Arithmetic Geometric Mean