Reverse Dependencies of statsmodels

The following projects have a declared dependency on statsmodels:

• tsfresh — tsfresh extracts relevant characteristics from time series
• tsfuse — Automated feature construction for multiple time series data
• tslumen — A library for Time Series exploratory data analysis
• tsma — (time series model analyses) This package offers tools for analyzing models that generate multivariate time series as output.
• tsml — A development sandbox for time series machine learning algorithms.
• TSmodel — AUTOCALCULATE ARIMA MODEL
• tspymfe — Univariate time-series expansion for Pymfe package
• tstoolbox — Command line script and Python library to manipulate time series.
• TSUtilities — Various utilities for time series forecasting.
• tswidgets — Some functions and datasets to work with time series
• tti — Trading Technical Indicators, python library. Where Traditional Technical Analysis and AI are met.
• tuanalyzes — no summary
• tui-dsg — everything you need for our jupyter notebooks
• TumorDecon — Deconvolution Methods for Digital Cytometry
• tuneup — Global optimizer comparison and combination
• turbustat — Statistics of Turbulence
• tw-experimentation — Wise AB platform
• u8darts — A python library for easy manipulation and forecasting of time series.
• u8timeseries — A collection of easy-to-use timeseries forecasting models
• UCTB — Urban Computing ToolBox
• uganda-uber-switching-reg — A robust estimator to machine learning prediction misclassification
• ugd — Drawing graphs uniformly at random subject to partition constraints (Partition Adjacency Matrix). Used for network testing.
• ukbb-py — An ensemble of functions for analysing UKBB records on DNA Nexus.
• ulrm — A module that can make Univariate Linear Regression Model
• unbiasedness — Functions for estimating unbiasedness regressions.
• unimortal — Tools to get inference from the Global Mortality Rate in Python
• unique-uncertainty — UNIQUE is a Python package for benchmarking uncertainty estimation and quantification methods for Machine Learning models predictions.
• unismod — no summary
• unitvelo — Temporally unified RNA velocity inference
• universal-portfolios — Collection of algorithms for online portfolio selection
• unpast — A novel method for unsupervised patient stratification.
• unsupervised-multimodal-trajectory-modeling — trains mixtures of state space models with expectation maximization
• urbansim — Platform for building statistical models of cities and regions
• urbansim-templates — UrbanSim extension for managing model steps
• urbansim-wfrc — Urbansim library originally by Paul Waddell, customized by WFRC Analytics
• urbantrips — A library to process public transit smart card data.
• url-image-module — Image Module of REACT
• validar-modelos — Ferramentas e Instruções para Validação de Modelos Clássicos
• validate-models — Tools and Instructions for Validation of Classical Models
• validmind — ValidMind Developer Framework
• vartests — Statistic tests for Value at Risk (VaR) Models.
• vbp — Value Based Prioritization
• vdeh — no summary
• vectice — Vectice Python library
• vectorlab — A lab for vectors.
• veda-lib — veda_lib is a Python library designed to streamline the data preprocessing and cleaning workflow for machine learning projects. It offers a comprehensive set of tools to handle common data preparation tasks
• velocycle — Bayesian model for RNA velocity estimation of periodic manifolds
• verifai — A toolkit for the formal design and analysis of systems that include artificial intelligence (AI) and machine learning (ML) components.
• verispy — Parses VCDB json data into a Pandas DataFrame and provides summary functions and basic enumeration plotting.
• vetiver — Version, share, deploy, and monitor models.
• vf-forecaster — A portable optimized time-series forecasting framework for Python
• vf-portalytics — A consistent interface for creating Machine Learning Models compatible with VisualFabriq environment
• views-stepshift — The code used to run modelling pipelines at ViEWS
• vimms — A framework to develop, test and optimise fragmentation strategies in LC-MS metabolomics.
• viprs — Variational Inference of Polygenic Risk Scores (VIPRS)
• viroconcom — ViroCon is a software to compute environmental contour
• vital-sqi — Signal quality control pipeline for electrocardiogram and photoplethysmogram
• vitalDSP — A comprehensive toolkit for Digital Signal Processing in healthcare applications.
• vitalSQI-toolkit — A toolkit for signal quality analysis of ECG and PPG signals
• vogel — vogel Python Package
• vortexasdk — Vortexa SDK
• voyagerpy — Python library for Voyager, the geo-spatialist R library.
• vplotly — A small package for plotting based on plotly. This package is accompanying the package vstats.
• VRAresultsTest — Set of tools to measure and run test laid out by the 1982 Voting Rights Amendment
• VSRstats — VSR statstics compute util
• vstats — A small Python package providing tools for statistics
• vtool-ibeis — vision tools for IBEIS
• wa-analyzer — Code for the Master of Applied Data Science course Data Analysis and Visualization
• wammodels — library for customization modeling .WA
• water-masses — Analysis of the northern European shelf seas
• wbia-vtool — Vtool - Image Tools for Wildbook IA
• we-factor-quad — Factor Quad, a data structure for factor analysis
• we-report — Wealth Engine ReportData Generator
• wearablehrv — Wearablehrv: A Python package for the validation of heart rate and heart rate variability in wearables.
• webviz-subsurface — Webviz config plugins for subsurface data
• weedout — no summary
• wetterdienst — Open weather data for humans
• wgcpy — Data analysis and PMML model framework!
• wildbook-ia — Wildbook IA (WBIA) - Machine learning service for the WildBook project
• wildboottest — Wild Cluster Bootstrap Inference for Linear Models in Python
• wiliot-deployment-tools — A library for interacting with Wiliot's Deployment Tools
• wisdem — Wind-Plant Integrated System Design & Engineering Model
• wisestork — Within-sample CNV calling
• wishbone-dev — Wishbone algorithm for identifying bifurcating trajectories from single-cell data
• witcher — Automated AI tool including: recommender system, deep Learnings ...
• woe-scoring — Weight Of Evidence Transformer and LogisticRegression model with scikit-learn API
• wqio — wqio: Water Quality Inflow/Outflow
• wrangle — Wrangle - Data Preparation for Deep Learning
• WSIPeruDB — Water Stable Isotope Database in Peru
• wuggy — Wuggy: A multilingual pseudoword generator
• wwdata — Data analysis package aimed at data obtained in the context of (waste)water
• wzyFunc — My Python Package
• xaiz — Explainable Artificial Intelligence (XAI) Library
• XBBO — A Python toolbox for performing Black-Box Optimization.
• xbout — Collect data from BOUT++ runs in python using xarray
• xclim — Climate indices computation package based on Xarray.
• xclone — Inference of clonal Copy Number Alterations in single cells
• xdatbus — A Python package enhancing VASP AIMD simulation
• xdeen — AI trading network for cryptocurrencies
• xeofs — Comprehensive EOF analysis in Python with xarray: A versatile, multidimensional, and scalable tool for advanced climate data analysis