Reverse Dependencies of statsmodels

The following projects have a declared dependency on statsmodels:

• rootwater — Python package to estimate root water uptake (RWU) from rhizosphere soil moisture dynamics and some tools to handle sap flow measurements
• ross-ml — ross-machine-learning
• roufcp — A python package for detecting gradual changepoint using Fuzzy Rough CP (roufCP)
• roux — Convenience functions.
• rpbp — Rp-Bp: Ribosome Profiling with Bayesian Predictions
• rqfactor — Ricequant factor engine
• rqpattr — ricequant performance attribution lib
• rsmtool — Rater scoring modeling tool
• rSTSF — Fast, accurate and explainable time series classification through randomization
• rtm-fast — A fast unification ds code package
• rtm-tsfresh — tsfresh extracts relevant characteristics from time series
• RTOC — RealTime OpenControl
• Rudraya — no summary
• ruins-app — Climate change and uncertainty explorer
• runml-checks — Package for validating your machine learning model and data
• safe-ds — A user-friendly library for Data Science in Python.
• safegraph-eval — Library for evaluating SafeGraph data
• Sagittarius-api-test — no summary
• salesforce-merlion — Merlion: A Machine Learning Framework for Time Series Intelligence
• sam — Time series anomaly detection and forecasting
• sam-ml-py — a library for ML programing created by Samuel Brinkmann
• sample-explorer — SampleExplorer: A tool for textual and gene set search against ARCHS4 data
• sample-size — A python module implementing power analysis to estimate sample size
• sample-statistics — A package for calculating weighted statistics on a set of samples.
• samplics — Select, weight and analyze complex sample data
• sax4bpm — Open source Python library for deriving explanations about business processes based on process,causal and XAI perspectives
• SC-search — Single-cell search tool
• scAAnet — An implementation of nonlinear archetypal analysis on single-cell RNA-seq data through autoencoder
• scAllele — A versatile tool for the detection and analysis of nucleotide variants in scRNA-seq
• scanpy — Single-Cell Analysis in Python.
• scapyp — A Python package for single-case data analysis.
• scarf — Scarf: A scalable tool for single-cell omics data analysis
• scBoolSeq — scBoolSeq: Linking scRNA-Seq Statistics and Boolean Dynamics.
• scbs — command line tool for the analysis of single-cell bisulfite-sequencing data
• scCloud — scRNA-Seq analysis tools that scale to millions of cells
• scCODA — A Dirichlet-Multinomial approach to identify compositional changes in count data.
• sccross — Single cell multi-omics cross modal generation, multi-omics simulation and perturbation
• SCDB-ML-app — A MACHINE LEARNING ANALYZER DEPLOYED INTO A WEBPAGE
• scdna-replication-tools — Code for analyzing single-cell replication dynamics
• scdrs — Single-cell disease-relevance score
• ScenarioReducer — Scenario Reduction Algorithms in Stochastic Programming
• scFates — scanpy compatible python suite for fast tree inference and advanced pseudotime downstream analysis
• scGCO — single-cell graph cuts optimization
• scgenome — Code for analyzing single cell whole genomes
• scglue — Graph-linked unified embedding for unpaired single-cell multi-omics data integration
• schimpy — Python package for SCHISM
• scientistmetrics — Python package for metrics and scoring : quantifying the quality of predictions
• SciFin — SciFin is a python package for Science and Finance.
• scikeo — Remote Sensing Tools
• scikit-datasets — Scikit-learn-compatible datasets
• scikit-diveMove — Python interface to R package diveMove
• scikit-hts — Hierarchical Time Series forecasting
• scikit-longitudinal — Scikit-longitudinal, an open-source Python lib for longitudinal data analysis, builds on Scikit-learn's foundation. It offers specialised tools to tackle challenges of repeated measures data, ideal for (med.) researchers, data scientists, & analysts.
• scikit-mobility — A toolbox for analyzing and processing mobility data.
• scikit-mobility-unofficial — A toolbox for analyzing and processing mobility data.
• scikit-na — Missing Values Analysis for Data Science
• scikit-posthocs — Statistical post-hoc analysis and outlier detection algorithms
• scilpy — Scilpy: diffusion MRI tools and utilities
• scimotf — no summary
• scipeds — A Python package for working with IPEDS data
• sciRED — single cell interpretable Residual Decomposition
• sciscripts — Scripts for controlling devices/running experiments/analyzing data
• scivae — no summary
• scludam — Star cluster detection and membership estimation based on GAIA data.
• scMDCF — Aligned Cross-modal Integration and Characterization of Single-Cell Multiomic Data with Deep Contrastive Learning
• SCNIC — A tool for finding and summarizing modules of highly correlated observations in compositional data
• scoary-2 — Scoary2: Associate genes with traits!
• score-card-model — Risk Score Card Model
• scorecardpipeline — 评分卡pipeline建模包，封装toad、scorecardpy、optbinning等评分卡建模相关组件，API风格与sklearn高度一致，自持自定义模型报告输出
• scorescanner — scorescanner helps you understand the main factors influencing the target of predictive tabular machine learning models.
• scperturb — Python package with E-distance tools for single-cell perturbation data analysis.
• scpi-pkg — The package computes point estimates and prediction intervals for Synthetic Control methods with multiple treated units and staggered adoption as proposed in Cattaneo, Feng, Palomba, and Titiunik (2024).
• scProject — Transfer learning framework for single cell gene expression analysis in Python
• scpy4reactome — python service for single cell analysis in Reactome
• scrapi — no summary
• scReGAT — A GAT-based computational framework to predict long-range gene regulatory relationships
• scsims — Scalable, Interpretable Deep Learning for Single-Cell RNA-seq Classification
• scUNAGI — A Python package for UNAGI
• scut-ssvep-aperiod — aperiod extract and ssvep measure
• scuteegfe — EEG Signal Feature Exacting, a wrapper of mne_features
• seabass — A hierarchical linear mixed model for analyzing CRISPR screen data.
• seaborn — Statistical data visualization
• SEAGAL — Spatial Enrichment Analysis of Gene Association using L-index
• seamm-util — seamm_util
• secimtools — 'Metabolomics tools from the SECIM project',
• seeline — DESCRIPTION
• segindex — Segregation Index
• segmentheepy-euro — Segmenthee library
• segretini-matplottini — Colorful recipes and utilities for Matplolib and Seaborn, to create publication-ready plots
• sekupy — Detergent for your dirty neuroimaging pipelines
• selective — feature selection library
• SelfCalibratingConformal — A Python implementation of Self-Calibrating Conformal Prediction
• selfish-hic — Hi-C Differential Analysis software created and maintained by the Ay Lab
• sensortoolkit — Library for evaluating air sensor data
• seqabpy — Sequential A/B Testing Framework in Python
• sequana — A set of standalone application and pipelines dedicated to NGS analysis
• serapis — Flood simulation model
• SESAMI — Characterization Tools for Porous Materials Using Nitrogen/Argon Adsorption
• sesd — Anomaly detection algorithm implemented at Twitter
• SEVtras — sEV-containing droplet identification in scRNA-seq data