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Statistical models with python using numpy and scipy. Currently covers linear regression (with ordinary, generalized and weighted least squares), robust linear regression, and generalized linear model, discrete models, time series analysis and other statistical methods.

...mlpy is available both for Python >=2.6 and Python 3.X.

This program was written to dimonstrate errors in transmission for a presentation on Claude Shannon's Noisy Channel Coding Theorem. It takes an input file, the probability of a bit being flipped, and, if specified, the size of the header of the file. The program was intended to take monochrome bitmap files as input, so that each bit refers to a pixel in the image and thus, it would be easy to see errors in the output file, as some of the pixels would be flipped; however, it will work on any...

This project hosts tools used for analysis of Gaussian Mixture Distributions (GMDs) which are used for statistical signal processing. The tools are libraries for implementing GMD operations and programs used to analyze properties of GMDs.

Worst Cases is a python script that enables calculations on worst case objects. Like a calculator operating on worst cases (e.g. [1,2,3]) rather than on real numbers (2.35) WARNING: This program is released as is, and has never been extensively teste

Measurement uncertainties with Python.

snlanalytic is a small Python script that takes a stem-and-leaf plot as input and returns basic statistics (sum, mean, median, mode) to the user.

This program generates customizable hyper-surfaces (multi-dimensional input and output) and samples data from them to be used further as benchmark for response surface modeling tasks or optimization algorithms.

Python module to track the overall median of a stream of values "on-line" in reasonably efficient fashion.

PGAF provides a framework tuned, user-specific genetic algorithms by handling I/O, UI, and parallelism. It is designed for optimizing functions that take a "very long time" to evaluate.

Classic Texas Hold'Em Poker game in python.