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Ergodicity Library: A Python toolkit for stochastic processes and ergodicity economics.

The Ergodicity Library is a comprehensive Python package designed for analyzing stochastic processes, with a particular focus on ergodicity economics. It offers powerful tools for:

• Simulating and visualizing various stochastic processes, including Brownian motion, Lévy processes, and custom-defined processes.
• Analyzing time averages and ensemble averages of stochastic processes.
• Implementing ergodic transformations and other key concepts from ergodicity economics.
• Fitting stochastic models to empirical data and estimating process parameters.
• Creating and training artificial agents for decision-making under uncertainty.
• Performing multi-core computations for efficient large-scale simulations.

Key Features:

• Object-oriented design with a flexible class hierarchy for stochastic processes.
• Seamless integration with popular scientific Python libraries like NumPy, SciPy, SymPy, and Matplotlib.
• Symbolic computation capabilities for stochastic calculus.
• Advanced tools for analyzing non-ergodic and heavy-tailed processes.
• Support for both Itô and non-Itô processes.
• Customizable configurations with sensible default parameters.

The library is ideal for researchers, students, and practitioners in disciplines such as economics, finance, physics, and applied mathematics. It bridges the gap between theoretical concepts in ergodicity economics and practical computational tools.

For more information, visit: www.ergodicitylibrary.com

Version: 0.3.1