Trimmed L-moments and L-comoments for robust statistics.
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Updated
Dec 15, 2025 - Python
Trimmed L-moments and L-comoments for robust statistics.
書籍『システム制御理論と統計的機械学習』のサポートページです。
Python scripts from paper Optimal cleaning for singular values of cross-covariance matrices, by Florent Benaych-Georges, Jean-Philippe Bouchaud, Marc Potters (see https://arxiv.org/abs/1901.05543)
Analyze global earthquake data from USGS via CLI. Fetch, filter, find recurrence intervals, and visualize trends.
This repo contains the necessary Python controller files that implement navigational control logic for robots in the Webots simulation environment. The controller files, reports, and videos were created during the Fall'23 Control of Mobile Robots elective course at USF.
This repository contains a Python package that implements Gaussian and Binomial distributions.
Experimental Verification of Monty Hall Problem
This repository is created in order to solve some proability assignment using python
Analyzed and studied different kinds of demographic factors that can affect the population in the United States
GeoPrior-v3: Physics-guided AI for geohazards
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Lenovo marka bilgisayarların fiyat istatistikleri
Python program to compute the probabilities of adding score when answering test questions randomly
Coding solutions for Probability and Statistics homework questions
Explore Mathematical Playground, housing essential Python algorithms for probability, statistics, dynamic programming, sorting, and searching.
An interactive Dash app for analyzing COVID-19 data using statistics and visualizations. Features include summary stats, probability analysis, and linear regression predictions with interactive charts. Built with Dash, Plotly, and Pandas.
A game of m, n, k-Tic-tac-toe. At the beginning the user chooses the values of m, n, k, and the type of AI that they will play against. Each type of AI can also play against each other.
Implementation of data-driven model falsification methods in Python.
Python module for performing sportsbook odds calculations
I did this project as part of my course work in statistical machine learning for my MS
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