Alternatives and similar repositories for bsts

Users that are interested in bsts are comparing it to the libraries listed below

• AngelPone / pyhts
  A python package for hierarchical forecasting, inspired by hts package in R.
  ☆29Updated 11 months ago
• takechanman1228 / Effective-Uplift-Modeling
  ☆25Updated last year
• xqnwang / conformalForecast
  Methods and tools for multistep-ahead time series conformal prediction.
  ☆44Updated 3 weeks ago
• rakshitha123 / WeeklyForecasting
  This repository contains the experiments related with a new baseline model that can be used in forecasting weekly time series. This model…
  ☆48Updated 3 years ago
• lavinei / pybats
  Bayesian time series forecasting and decision analysis
  ☆120Updated 2 years ago
• FMenchetti / CausalArima
  An R package to estimate the effect of interventions on univariate time series using ARIMA models
  ☆25Updated last year
• DarkEyes / VLTimeSeriesCausality
  A framework to infer causality on a pair of time series of real numbers based on Variable-lag Granger causality and transfer entropy.
  ☆57Updated last year
• ModelOriented / SAFE
  Surrogate Assisted Feature Extraction
  ☆37Updated 4 years ago
• Valdecy / pyInterDemand
  A python Library for Intermittent Demand Methods: Croston, SBA, SBJ, TSB, HES, LES and SES
  ☆39Updated 2 years ago
• rabia174 / ConformaSight
  Conformal Prediction-Based Global and Model Agnostic Explainability for Classification tasks.
  ☆26Updated last year
• Nixtla / datasetsforecast
  Datasets for time series forecasting
  ☆118Updated last week
• luisroque / bayesian_time_series
  Machine Learning models using a Bayesian approach and often PyMC3
  ☆25Updated 5 years ago
• mikekeith52 / scalecast-examples
  Examples of the application of individual scalecast models
  ☆44Updated 2 years ago
• ajayarunachalam / Deep_XF
  Package towards building Explainable Forecasting and Nowcasting Models with State-of-the-art Deep Neural Networks and Dynamic Factor Mode…
  ☆118Updated 3 years ago
• PlaytikaOSS / uplift-analysis
  A Python library that implements scoring utilities, analysis strategies, and visualization methods which can serve uplift modeling use-ca…
  ☆24Updated 2 years ago
• ChadFulton / scipy2022-bayesian-time-series
  Bayesian Estimation and Forecasting of Time Series in statsmodels, for Scipy 2022 conference
  ☆25Updated 3 years ago
• predict-idlab / cct-cmc
  Implementation of Conformal Convolution T-learner (CCT) and Conformal Monte Carlo (CMC) learner
  ☆17Updated 8 months ago
• lixixibj / DeepVARwT-data-code
  ☆20Updated 3 months ago
• StatMixedML / Hyper-Trees
  Forecasting with Hyper-Trees
  ☆20Updated 6 months ago
• mtorabirad / MLBoost
  ☆17Updated last year
• andrewtavis / causeinfer
  Machine learning based causal inference/uplift in Python
  ☆62Updated 2 weeks ago
• raz1470 / causal_ai
  This project introduces Causal AI and how it can drive business value.
  ☆54Updated last year
• larsroemheld / causalinf_ex_elasticity
  A full example for causal inference on real-world retail data, for elasticity estimation
  ☆52Updated 4 years ago
• StatMixedML / CatBoostLSS
  An extension of CatBoost to probabilistic modelling
  ☆149Updated 2 years ago
• zalandoresearch / ACIC23-competition
  Data for and description of the ACIC 2023 data competition
  ☆32Updated 2 years ago
• tblume1992 / Seance
  Wrapper around MLForecast for more plug and play forecasting
  ☆10Updated 2 years ago
• OVVO-Financial / NNS
  Nonlinear Nonparametric Statistics
  ☆101Updated last week
• astrogilda / tsbootstrap
  tsbootstrap: generate bootstrapped time series samples in Python
  ☆88Updated 7 months ago
• yotambraun / APDTFlow
  APDTFlow is a modern and extensible forecasting framework for time series data that leverages advanced techniques including neural ordina…
  ☆42Updated 2 months ago
• jehangiramjad / tslib
  Time Series Forecasting and Imputation
  ☆48Updated 4 years ago