Reverse Dependencies of statsmodels

The following projects have a declared dependency on statsmodels:

• sfdc-merlion — Merlion: A Machine Learning Framework for Time Series Intelligence
• sforecast — A framework for running forecasting models within a sliding/expanding window out-of-sample forecast fit (train/test) and prediction (forecasts). The package includes support of classical forecasting models, SK Learn supervised learning ML models, and TensorFlow deep learning models.
• sh-powerpeak-predict — Sunghan Power Peak Prediction
• sh-weather-predict — Sunghan Weather Prediction
• shap-app — A comprehensive application for interpreting machine learning models using SHAP values
• sherlockpipe — Search for Hints of Exoplanets fRom Lightcurves Of spaCe based seeKers
• ShiftAI — ShiftAI - smart energy management for Home Assistant with load shifting recommendations.
• shinybroker — Python API for Interactive Brokers
• shipgrav — Functions for marine gravity data processing and reduction
• siat — Securities Investment Analysis Tools (siat)
• siate — Securities Investment Analysis Tools in English (SIATE)
• sigmet — A Python package to find and measure negative price shocks in financial time-series data
• sigproextractor — Extracts mutational signatures from mutational catalogues
• SigProfilerAssignment — Mutational signatures attribution and decomposition tool
• SigProfilerClusters — SigProfilerClusters tool
• SigProfilerExtractor — Extracts mutational signatures from mutational catalogues
• SigProfilerHotSpots — SigProfilerHotSpots tool
• SigProfilerTopography — SigProfilerTopography provides topography analyses for substitutions, dinucleotides and indels for all given samples.
• SigProfilerTopographyCombiner — SigProfilerTopographyCombiner combines separate SigProfilerTopography runs.
• sigproSS — Decomposes mutational catalogues to mutational signatures
• sigtech — SigTech Python SDK
• siibra-jugex — siibra-jugex - Differential analysis of gene expression in brain regions using the siibra framework
• silicone — Automated filling of detail in reported emission scenarios
• Simba-UW-no-tf — Toolkit for computer classification of complex social behaviors in experimental animals
• Simba-UW-tf — Toolkit for computer classification of complex social behaviors in experimental animals
• Simba-UW-tf-dev — Toolkit for computer classification of complex social behaviors in experimental animals
• simd-structts — SIMD StuctTS Model with various backends
• simplevec — SimpleVec: Elementary Examples of Vector Modeling
• simpliml — Machine Learning, Artificial Intelligence, Mathematics
• SimplyEDA — A simple library for exploratory data analysis
• simpml — SimpML is an open-source, no/low-code machine learning library in Python that simplifies and automates machine learning workflows.
• simvi — Spatial Interaction Modeling using Variational Inference
• singlecellmultiomics — Tools to deal with one or more measurements from single cells
• singlefactortest — 单因子的测试（日级别and分钟级别）
• singletrader — a package for backtesting and factor analysis
• sixsigmaspc — Statistical Process Control library
• skcredit — scorecard
• skforecast — Skforecast is a Python library for time series forecasting using machine learning models. It works with any regressor compatible with the scikit-learn API, including popular options like LightGBM, XGBoost, CatBoost, Keras, and many others.
• sklearn-contrib-py-earth — A Python implementation of Jerome Friedman's Multivariate Adaptive Regression Splines.
• sklearn-linear-model-modification — Wraps sklearn linear_model regression functions to allow Drop1, Add1, and VIF calculations
• sklearn-viz — no summary
• sklearn2 — small scikit-learn extension
• skpro — A unified framework for tabular probabilistic regression, time-to-event prediction, and probability distributions in python
• skquantreg — Scikit wrapper for quantreg
• skrub — Prepping tables for machine learning
• sktime — A unified Python toolbox for machine learning with time series
• sktime-legacy — scikit-learn compatible toolbox for learning with time series/panel data
• sktools — Tools to extend sklearn
• SL-regression-quality — simple linear regression quality
• slade — A package for doing great things!
• sleapyfaces — A package for extracting facial expressions from SLEAP analyses
• sleepkit — AI driven sleep monitoring kit for ultra low-power wearables.
• slickml — SlickML: Slick Machine Learning in Python
• slidingRP — Quality metric from spike trains
• Slpapy — Spatial_lipomic_and_proteomic_analysis
• smadi — Add a short description here!
• SMAK — A MicroAnalysis Toolkit.
• smana — Repairing tool for time series with weekly seasonality
• SMART-BS-Seq — Specific Methylation Analysis and Report Tool 2
• smartdataai — SmartDataAI: Intelligent Data Cleaning, Transformation, Charting, and Analysis with LLM
• smartdataai-test — A package for SmartData management and operations.
• smartpyml — smartpyml: A Comprehensive Machine Learning Library
• smartstats — Pretty Statistics
• smc-movement-models — Projet pour le cours Hidden Markov models and Sequential Monte-Carlo methods de l'ENSAE.
• smeagol-bio — no summary
• smqpp — Smartseq2 preprocessing toolkit
• SNAF — A Python package to predict, prioritize and visualize splicing derived neoantigens, including MHC-bound peptides (T cell antigen) and altered surface protein (B cell antigen)
• SnapFISH — A computational pipeline to identify chromatin loops from multiplexed DNA FISH data
• SnapHiC-D — A computational pipeline to identify differential chromatin contacts from single cell Hi-C data
• snetcr — Pairwise distance calculation and neighborhood enrichment analysis of TCR repertoires
• snowflake-snowpark-python — Snowflake Snowpark for Python
• sntn — Sum of a normal and a truncated Normal (SNTN)
• soam — Tools for time series analysis, plotting and reporting.
• socialdataanalysis — Funções personalizadas para análise de dados nas ciências sociais.
• SoEasyData — 快速获取数据的简洁程序库
• soft-search — searching for software promises in grant applications
• solarforecastarbiter — Core framework for Solar Forecast Arbiter
• solas-ai — A Python Library of Curated Disparity Testing Metrics for Use in Real-World Settings
• somata — State-space Oscillator Modeling And Time-series Analysis
• SPACEc — SPatial Analysis for CodEX data (SPACEc)
• spaco — Smooth and probablistic PARAFAC decomposition with covariates
• spacr — Spatial phenotype analysis of crisp screens (SpaCr)
• sparsecca — A full implementation of sparse CCA.
• spartan2 — collection of data mining algorithms on big graphs and time series
• spateo-release — Spateo: multidimensional spatiotemporal modeling of single-cell spatial transcriptomics
• spatialaudiometrics — For calculating spatial audio metrics
• SpatialDM — SpatialDM: Spatial co-expression Detected by bivariate Moran
• spd-trading — Estimates the Risk Neutral Density and Historical Density of an underlying and suggests trading intervals based on the Pricing Kernel.
• spearmint — Refreshing hypothesis testing in python!
• specification-curve — Specification_Curve
• spflow — Sum Product Flow: An Easy and Extensible Library for Sum-Product Networks
• sphinx-gallery — A Sphinx extension that builds an HTML gallery of examples from any set of Python scripts.
• sphractal — Package to estimate fractal dimension of 3D surfaces formed from overlapping spheres via box-counting algorithm.
• sphynxml — no summary
• spi-pack — A module to run analysis
• spider-st — Identifying spatially variable interactions
• spiderYa — Identifying spatially variable interactions
• spiketools — Module for analyzing spiking data.
• spinspotter — Fast, autocorrelation-based algorithm for finding stellar rotation periods from light curves.
• splineplot — no summary