80 Repositories
Python statistical-validity Libraries
Lightning ⚡️ fast forecasting with statistical and econometric models.
Nixtla Statistical ⚡️ Forecast Lightning fast forecasting with statistical and econometric models StatsForecast offers a collection of widely used uni
Seaborn is one of the go-to tools for statistical data visualization in python. It has been actively developed since 2012 and in July 2018, the author released version 0.9. This version of Seaborn has several new plotting features, API changes and documentation updates which combine to enhance an already great library. This article will walk through a few of the highlights and show how to use the new scatter and line plot functions for quickly creating very useful visualizations of data.
12_Python_Seaborn_Module Introduction 👋 From the website, “Seaborn is a Python data visualization library based on matplotlib. It provides a high-lev
My Solutions to 120 commonly asked data science interview questions.
Data_Science_Interview_Questions Introduction 👋 Here are the answers to 120 Data Science Interview Questions The above answer some is modified based
BASH - Biomechanical Animated Skinned Human
We developed a method animating a statistical 3D human model for biomechanical analysis to increase accessibility for non-experts, like patients, athletes, or designers.
This repo contains a powerful tool made using python which is used to visualize, analyse and finally assess the quality of the product depending upon the given observations
📈 Statistical Quality Control 📉 This repo contains a simple but effective tool made using python which can be used for quality control in statistica
This repo contains a simple but effective tool made using python which can be used for quality control in statistical approach.
This repo contains a powerful tool made using python which is used to visualize, analyse and finally assess the quality of the product depending upon the given observations
Combinatorial model of ligand-receptor binding
Combinatorial model of ligand-receptor binding The binding of ligands to receptors is the starting point for many import signal pathways within a cell
Statistical & Probabilistic Analysis of Store Sales, University Survey, & Manufacturing data
Statistical_Modelling Statistical & Probabilistic Analysis of Store Sales, University Survey, & Manufacturing data Statistical Methods for Decision Ma
Ab testing - basically a statistical test in which two or more variants
Ab testing - basically a statistical test in which two or more variants
Synthetic data need to preserve the statistical properties of real data in terms of their individual behavior and (inter-)dependences
Synthetic data need to preserve the statistical properties of real data in terms of their individual behavior and (inter-)dependences. Copula and functional Principle Component Analysis (fPCA) are statistical models that allow these properties to be simulated (Joe 2014). As such, copula generated data have shown potential to improve the generalization of machine learning (ML) emulators (Meyer et al. 2021) or anonymize real-data datasets (Patki et al. 2016).
Jupyter notebooks for the book "The Elements of Statistical Learning".
This repository contains Jupyter notebooks implementing the algorithms found in the book and summary of the textbook.
Statistical Rethinking course winter 2022
Statistical Rethinking (2022 Edition) Instructor: Richard McElreath Lectures: Uploaded Playlist and pre-recorded, two per week Discussion: Online, F
NLG evaluation via Statistical Measures of Similarity: BaryScore, DepthScore, InfoLM
NLG evaluation via Statistical Measures of Similarity: BaryScore, DepthScore, InfoLM Automatic Evaluation Metric described in the papers BaryScore (EM
Statistical Random Number Generator Attack Against The Kirchhoff-law-johnson-noise (Kljn) Secure Key Exchange Protocol
Statistical Random Number Generator Attack Against The Kirchhoff-law-johnson-noise (Kljn) Secure Key Exchange Protocol
Specification language for generating Generalized Linear Models (with or without mixed effects) from conceptual models
tisane Tisane: Authoring Statistical Models via Formal Reasoning from Conceptual and Data Relationships TL;DR: Analysts can use Tisane to author gener
This repository contains the exercises and its solution contained in the book "An Introduction to Statistical Learning" in python.
An-Introduction-to-Statistical-Learning This repository contains the exercises and its solution contained in the book An Introduction to Statistical L
Python algorithm to determine the optimal elevation threshold of a GNSS receiver, by using a statistical test known as the Brown-Forsynthe test.
Levene and Brown-Forsynthe: Test for variances Application to Global Navigation Satellite Systems (GNSS) Python algorithm to determine the optimal ele
PCACE: A Statistical Approach to Ranking Neurons for CNN Interpretability
PCACE: A Statistical Approach to Ranking Neurons for CNN Interpretability PCACE is a new algorithm for ranking neurons in a CNN architecture in order
Statistical-Rethinking-with-Python-and-PyMC3 - Python/PyMC3 port of the examples in " Statistical Rethinking A Bayesian Course with Examples in R and Stan" by Richard McElreath
Statistical Rethinking with Python and PyMC3 This repository has been deprecated in favour of this one, please check that repository for updates, for
Statistical Rethinking: A Bayesian Course Using CmdStanPy and Plotnine
Statistical Rethinking: A Bayesian Course Using CmdStanPy and Plotnine Intro This repo contains the python/stan version of the Statistical Rethinking
whylogs: A Data and Machine Learning Logging Standard
whylogs: A Data and Machine Learning Logging Standard whylogs is an open source standard for data and ML logging whylogs logging agent is the easiest
This app displays interesting statistical weather records and trends which can be used in climate related research including study of global warming.
This app displays interesting statistical weather records and trends which can be used in climate related research including study of global warming.
This tool allows to gather statistical profile of CPU usage of mixed native-Python code.
Sampling Profiler for Python This tool allows to gather statistical profile of CPU usage of mixed native-Python code. Currently supported platforms ar
Monitor the stability of a pandas or spark dataframe ⚙︎
Population Shift Monitoring popmon is a package that allows one to check the stability of a dataset. popmon works with both pandas and spark datasets.
Python script to combine the statistical results of a TOPAS simulation that was split up into multiple batches.
topas-merge-simulations Python script to combine the statistical results of a TOPAS simulation that was split up into multiple batches At the top of t
A simple bot that lives in your Telegram group, logging messages to a Postgresql database and serving statistical tables and plots to users as Telegram messages.
telegram-stats-bot Telegram-stats-bot is a simple bot that lives in your Telegram group, logging messages to a Postgresql database and serving statist
Research code for the paper "Variational Gibbs inference for statistical estimation from incomplete data".
Variational Gibbs inference (VGI) This repository contains the research code for Simkus, V., Rhodes, B., Gutmann, M. U., 2021. Variational Gibbs infer
Exact algorithm for computing two-sided statistical tolerance intervals under a normal distribution assumption using Python.
norm-tol-int Exact algorithm for computing two-sided statistical tolerance intervals under a normal distribution assumption using Python. Methods The
Statistical tests for the sequential locality of graphs
Statistical tests for the sequential locality of graphs You can assess the statistical significance of the sequential locality of an adjacency matrix
A Python 3 package for state-of-the-art statistical dimension reduction methods
direpack: a Python 3 library for state-of-the-art statistical dimension reduction techniques This package delivers a scikit-learn compatible Python 3
Learning kernels to maximize the power of MMD tests
Code for the paper "Generative Models and Model Criticism via Optimized Maximum Mean Discrepancy" (arXiv:1611.04488; published at ICLR 2017), by Douga
A Semi-Intelligent ChatBot filled with statistical and economical data for the Premier League.
MONEYBALL - ChatBot Module: 4006CEM, Class: B, Group: 5 Contributors: Jonas Djondo Roshan Kc Cole Samson Daniel Rodrigues Ihteshaam Naseer Kind remind
A statistical library designed to fill the void in Python's time series analysis capabilities, including the equivalent of R's auto.arima function.
pmdarima Pmdarima (originally pyramid-arima, for the anagram of 'py' + 'arima') is a statistical library designed to fill the void in Python's time se
A statistical library designed to fill the void in Python's time series analysis capabilities, including the equivalent of R's auto.arima function.
pmdarima Pmdarima (originally pyramid-arima, for the anagram of 'py' + 'arima') is a statistical library designed to fill the void in Python's time se
vartests is a Python library to perform some statistic tests to evaluate Value at Risk (VaR) Models
vartests is a Python library to perform some statistic tests to evaluate Value at Risk (VaR) Models, such as: T-test: verify if mean of distribution i
Statistical and Algorithmic Investing Strategies for Everyone
Eiten - Algorithmic Investing Strategies for Everyone Eiten is an open source toolkit by Tradytics that implements various statistical and algorithmic
Convoys is a simple library that fits a few statistical model useful for modeling time-lagged conversions.
Convoys is a simple library that fits a few statistical model useful for modeling time-lagged conversions. There is a lot more info if you head over to the documentation. You can also take a look at this blog post about Convoys.
Transform ML models into a native code with zero dependencies
m2cgen (Model 2 Code Generator) - is a lightweight library which provides an easy way to transpile trained statistical models into a native code
AI-UPV at IberLEF-2021 DETOXIS task: Toxicity Detection in Immigration-Related Web News Comments Using Transformers and Statistical Models
AI-UPV at IberLEF-2021 DETOXIS task: Toxicity Detection in Immigration-Related Web News Comments Using Transformers and Statistical Models Description
Grounding Representation Similarity with Statistical Testing
Grounding Representation Similarity with Statistical Testing This repo contains code to replicate the results in our paper, which evaluates representa
Analysis code and Latex source of the manuscript describing the conditional permutation test of confounding bias in predictive modelling.
Git repositoty of the manuscript entitled Statistical quantification of confounding bias in predictive modelling by Tamas Spisak The manuscript descri
Survival analysis (SA) is a well-known statistical technique for the study of temporal events.
DAGSurv Survival analysis (SA) is a well-known statistical technique for the study of temporal events. In SA, time-to-an-event data is modeled using a
Creating a statistical model to predict 10 year treasury yields
Predicting 10-Year Treasury Yields Intitially, I wanted to see if the volatility in the stock market, represented by the VIX index (data source), had
statDistros is a Python library for dealing with various statistical distributions
StatisticalDistributions statDistros statDistros is a Python library for dealing with various statistical distributions. Now it provides various stati
Scalable implementation of Lee / Mykland (2012) and Ait-Sahalia / Jacod (2012) Jump tests for noisy high frequency data
JumpDetectR Name of QuantLet : JumpDetectR Published in : 'To be published as "Jump dynamics in high frequency crypto markets"' Description : 'Scala
Statistical Analysis 📈 focused on statistical analysis and exploration used on various data sets for personal and professional projects.
Statistical Analysis 📈 This repository focuses on statistical analysis and the exploration used on various data sets for personal and professional pr
Cockpit is a visual and statistical debugger specifically designed for deep learning.
Cockpit: A Practical Debugging Tool for Training Deep Neural Networks
Re-implementation of the Noise Contrastive Estimation algorithm for pyTorch, following "Noise-contrastive estimation: A new estimation principle for unnormalized statistical models." (Gutmann and Hyvarinen, AISTATS 2010)
Noise Contrastive Estimation for pyTorch Overview This repository contains a re-implementation of the Noise Contrastive Estimation algorithm, implemen
Code to run experiments in SLOE: A Faster Method for Statistical Inference in High-Dimensional Logistic Regression.
Code to run experiments in SLOE: A Faster Method for Statistical Inference in High-Dimensional Logistic Regression. Not an official Google product. Me
Statsmodels: statistical modeling and econometrics in Python
About statsmodels statsmodels is a Python package that provides a complement to scipy for statistical computations including descriptive statistics an
Probabilistic Programming in Python: Bayesian Modeling and Probabilistic Machine Learning with Aesara
PyMC3 is a Python package for Bayesian statistical modeling and Probabilistic Machine Learning focusing on advanced Markov chain Monte Carlo (MCMC) an
Scalable, event-driven, deep-learning-friendly backtesting library
...Minimizing the mean square error on future experience. - Richard S. Sutton BTGym Scalable event-driven RL-friendly backtesting library. Build on
Platform for building statistical models of cities and regions
UrbanSim UrbanSim is a platform for building statistical models of cities and regions. These models help forecast long-range patterns in real estate d
Enabling easy statistical significance testing for deep neural networks.
deep-significance: Easy and Better Significance Testing for Deep Neural Networks Contents ⁉️ Why 📥 Installation 🔖 Examples Intermezzo: Almost Stocha
PyStan, a Python interface to Stan, a platform for statistical modeling. Documentation: https://pystan.readthedocs.io
PyStan PyStan is a Python interface to Stan, a package for Bayesian inference. Stan® is a state-of-the-art platform for statistical modeling and high-
Statistical package in Python based on Pandas
Pingouin is an open-source statistical package written in Python 3 and based mostly on Pandas and NumPy. Some of its main features are listed below. F
Describing statistical models in Python using symbolic formulas
Patsy is a Python library for describing statistical models (especially linear models, or models that have a linear component) and building design mat
Python Library for learning (Structure and Parameter) and inference (Statistical and Causal) in Bayesian Networks.
pgmpy pgmpy is a python library for working with Probabilistic Graphical Models. Documentation and list of algorithms supported is at our official sit
Probabilistic reasoning and statistical analysis in TensorFlow
TensorFlow Probability TensorFlow Probability is a library for probabilistic reasoning and statistical analysis in TensorFlow. As part of the TensorFl
A statistical library designed to fill the void in Python's time series analysis capabilities, including the equivalent of R's auto.arima function.
pmdarima Pmdarima (originally pyramid-arima, for the anagram of 'py' + 'arima') is a statistical library designed to fill the void in Python's time se
Implementation of Kalman Filter in Python
Kalman Filter in Python This is a basic example of how Kalman filter works in Python. I do plan on refactoring and expanding this repo in the future.
Multiple Pairwise Comparisons (Post Hoc) Tests in Python
scikit-posthocs is a Python package that provides post hoc tests for pairwise multiple comparisons that are usually performed in statistical data anal
Probabilistic Programming and Statistical Inference in PyTorch
PtStat Probabilistic Programming and Statistical Inference in PyTorch. Introduction This project is being developed during my time at Cogent Labs. The
PyStan, a Python interface to Stan, a platform for statistical modeling. Documentation: https://pystan.readthedocs.io
PyStan NOTE: This documentation describes a BETA release of PyStan 3. PyStan is a Python interface to Stan, a package for Bayesian inference. Stan® is
Module for statistical learning, with a particular emphasis on time-dependent modelling
Operating system Build Status Linux/Mac Windows tick tick is a Python 3 module for statistical learning, with a particular emphasis on time-dependent
An open-source plotting library for statistical data.
Lets-Plot Lets-Plot is an open-source plotting library for statistical data. It is implemented using the Kotlin programming language. The design of Le
Declarative statistical visualization library for Python
Altair http://altair-viz.github.io Altair is a declarative statistical visualization library for Python. With Altair, you can spend more time understa
Statistical data visualization using matplotlib
seaborn: statistical data visualization Seaborn is a Python visualization library based on matplotlib. It provides a high-level interface for drawing
An open-source plotting library for statistical data.
Lets-Plot Lets-Plot is an open-source plotting library for statistical data. It is implemented using the Kotlin programming language. The design of Le
Declarative statistical visualization library for Python
Altair http://altair-viz.github.io Altair is a declarative statistical visualization library for Python. With Altair, you can spend more time understa
Statistical data visualization using matplotlib
seaborn: statistical data visualization Seaborn is a Python visualization library based on matplotlib. It provides a high-level interface for drawing
Statsmodels: statistical modeling and econometrics in Python
About statsmodels statsmodels is a Python package that provides a complement to scipy for statistical computations including descriptive statistics an
Was an interactive continuous Python profiler.
☠ This project is not maintained anymore. We highly recommend switching to py-spy which provides better performance and usability. Profiling The profi
Statsmodels: statistical modeling and econometrics in Python
About statsmodels statsmodels is a Python package that provides a complement to scipy for statistical computations including descriptive statistics an
Probabilistic Programming in Python: Bayesian Modeling and Probabilistic Machine Learning with Theano
PyMC3 is a Python package for Bayesian statistical modeling and Probabilistic Machine Learning focusing on advanced Markov chain Monte Carlo (MCMC) an
Multi-class confusion matrix library in Python
Table of contents Overview Installation Usage Document Try PyCM in Your Browser Issues & Bug Reports Todo Outputs Dependencies Contribution References
Python Library for learning (Structure and Parameter) and inference (Statistical and Causal) in Bayesian Networks.
pgmpy pgmpy is a python library for working with Probabilistic Graphical Models. Documentation and list of algorithms supported is at our official sit
Statistical data visualization using matplotlib
seaborn: statistical data visualization Seaborn is a Python visualization library based on matplotlib. It provides a high-level interface for drawing
Declarative statistical visualization library for Python
Altair http://altair-viz.github.io Altair is a declarative statistical visualization library for Python. With Altair, you can spend more time understa