Reverse Dependencies of statsmodels

The following projects have a declared dependency on statsmodels:

• enhancesa — Python micro-package for enhanced statistical analysis
• Enrich2 — Analysis program for calculating variant scores from deep mutational scanning data.
• enrichm — enrichm is a toolbox for comparing the functional composition of population genomes
• enstools — no summary
• ep-stats — Statistical package to evaluate ab tests in experimentation platform.
• epicas — An AutoML framework designed for epidemiological forecasting
• epidtool — A Python toolkit for analysis, modelling and forecasting Epidemic
• epilearn — A Pytorch library for machine learning in epidemic modeling
• epilogos — Information-theoretic navigation of multi-tissue functional genomic annotations
• epimargin — Toolkit for estimating epidemiological metrics and evaluating public health and economic policies.
• epiout — EpiOut: outlier detection for DNA accesibility data.
• epydemics — A module for modeling and analyzing epidemic data.
• epyestim — no summary
• eqsormo — Equilibrium sorting models in Python
• equipy — Equipy is a tool for fast, online fairness calibration
• ergodicity — A Python library for ergodicity economics and time-average analysis.
• eristropy — EristroPy: End-to-end entropy analysis of time series signals
• ern-backtester — Ernest Backtest Framework Library
• ertk — Tools for process emotion recognition datasets, extracting features, and running experiments.
• Eskapade — Eskapade modular analytics
• esmtools — a toolbox for Earth System Model analysis
• estout — Collect regression results and export them to LaTex and pdf
• estyp — Extended Statistical Toolkit Yet Practical
• EtaML — An automated machine learning platform with a focus on explainability
• etna — ETNA is the first python open source framework of T-Bank AI Center. It is designed to make working with time series simple, productive, and fun.
• etna-ts — ETNA is the first python open source framework of Tinkoff.ru AI Center. It is designed to make working with time series simple, productive, and fun.
• etradebot — A Python-based trading bot for the E-Trade platform
• ev-fleet-sim — This software computes the electrical energy requirements of a fleet of vehicles. It also determines how much of this energy can be offset by renewable energy.
• evalml — an AutoML library that builds, optimizes, and evaluates machine learning pipelines using domain-specific objective functions
• event-study-toolkit — A package for conducting event studies
• eventstudy — Event Study package is an open-source python project created to facilitate the computation of financial event study analysis.
• evidently — Open-source tools to analyze, monitor, and debug machine learning model in production.
• ewstools — Python package to compute early warning signals (EWS)
• ExMechEva — Evaluation of experimental mechanics data
• EXOTIC — EXOTIC: EXOplanet Transit Interpretation Code
• exoTras — exosome-containing droplet identification and source tracking in scRNA-seq data
• expAscribe — ExpAscribe: a causal inference framework for quantitative experiment ascription and its derivative process. Documentation: https://seabirdshore.github.io/EAdocs/
• experimentkit — A toolkit for easily running research experiments
• explainitall — no summary
• ExploriPy — Pre-Modelling Analysis of the data by doing various exploratory data analysis and Statistical Test
• F4RATK — A Fama/French Finance Factor Regression Analysis Toolkit.
• fabric-genetics — FABRIC (Functional Alteration Bias Recovery In Coding-regions) is a framework for detecting genes showing functional alteration bias.
• factor-analyser — A tool for factor development and analysis.
• faim — FAIM (FAir Interpolation Method), described in "Beyond Incompatibility: Interpolation between Mutually
• fairaudit — This package enables fairness auditing with statistical guarantees.
• faktotum — Extracting information from unstructured text.
• fast-causal-inference — fast causal inference package
• fast-explain — Fit Fast, Explain Fast
• fastats — A pure Python library for benchmarked, scalable numerics using numba
• fastnorm — Fast evaluation of multivariate normal distribution
• fastrepl — Fast Run-Eval-Polish Loop for LLM App
• fasttenet — FastTENET
• fba — Tools for single-cell feature barcoding analysis
• fba-quant — FBA Quant
• fbnlab-preview — Python library for performance measurement of Finbourne apps
• fcutils — bunch of utility functions
• fdhpy — Implementations of FDHI Project Fault Displacement Models
• featransform — Featransform is an automated feature engineering framework for Supervised Machine Learning
• feature-clock — Feature Clock, provides visualizations that eliminate the need for multiple plots to inspect the influence of original variables in the latent space. Feature Clock enhances the explainability and compactness of visualizations of embedded data.
• feature-engine — Feature engineering and selection package with Scikit-learn's fit transform functionality
• feature-selection-toolkit — A comprehensive toolkit for performing various feature selection techniques in machine learning.
• FeatureInsight — project description
• fed3bandit — Package to analyze FED3Bandit files.
• fed3live — Package to analyze fed3 files.
• fedcore — Federated learning core library
• fedot — Automated machine learning framework for composite pipelines
• fedot-example-test — Evolutionary structural learning framework FEDOT
• feyn — Feyn is a symbolic regression package named after Richard Feynman, that uses the QLattice as a simulator to generate models.
• fgclustering — Forest-Guided Clustering - Explainability method for Random Forest models.
• FIBTracking — Python module for FIB/SEM fiducial tracking
• fifids — data science for swiss cheese brains
• fightchurn — Code from the book Fighting Churn With Data
• FillingTimeSeries — Filling Time series: Package to fill missing values in geophysical time series in Python
• filter-stations — Making it easier to navigate and clean station data
• FinaleToolkit — FinaleToolkit is a package and standalone program to extract fragmentation features of cell-free DNA from paired-end sequencing data.
• finance-byu — Classes and functions for FIN 585 and finance research at Brigham Young University
• financiallib — Financial-Lib: A Library for Financial Data Analysis and Pre-Processing.
• finbright-utils — finbright private utils package
• findatapy — Market data library
• FineST — FineST: Fine-grained Spatial Transcriptomic
• fings — Filters for Next Generation Sequencing
• finlab-crypto — A backtesting framework for crytpo currency
• finstmt — Contains classes to work with financial statement data. Can calculate free cash flows and help project financial statements.
• fintoolkit — Financial Toolkit
• FIREcaller — Python library for detecting Frequently Interacting REgions (FIREs) from Hi-C data
• FIRSTBEATLU — This package contains several methods for calculating Conditional Average Treatment Effects
• fiser-tools — Personal DS tools
• fishersapi — fishersapi: An API for applying a fast Fisher's Exact Test to variable pairs in pandas DataFrames
• FishTaco — FishTaco: a metagenomic computational framework, aiming to identify the taxa that are driving functional shifts in microbiomes.
• fisspy — fisspy: Python analysis tools for GST/FISS
• fitgrid — Mass multiple regression manager
• fitPhylo — A package for inferring CNA fitness evolutionary trees and CNAs' evolutionary efficiency.
• FixedEffectModel — Solutions to linear model with high dimensional fixed effects.
• FixedEffectModelPyHDFE — Solutions to linear model with high dimensional fixed effects.
• fklearn — Functional machine learning
• FLAI-CAUSAL — Library to creat causal model and mitigate the bias.
• FLAML — A fast library for automated machine learning and tuning
• flexcv — Easy and flexible nested cross validation for tabular data in python.
• FLOCK-GPS — A package for extracting metrics from group movement GPS data
• fluidai-sanatio — Run different validation tests on machine learning models.