helske/KFAS

StateSpaceModels.jl is a Julia package for time-series analysis using state-space models.

{mvgam} R 📦 to fit Dynamic Bayesian Generalized Additive Models for multivariate modeling and forecasting

Forecasting Functions for Time Series and Linear Models

A Python package for probabilistic state space modeling with JAX

Toolkit for the estimation of hierarchical Bayesian vector autoregressions. Implements hierarchical prior selection for conjugate priors in the fashion of Giannone, Lenza & Primiceri (2015). Allows for the computation of impulse responses and forecasts and provides functionality for assessing results.

Package implementing common state-space routines.

R package to accompany Time Series Analysis and Its Applications: With R Examples -and- Time Series: A Data Analysis Approach Using R

Tidy time series forecasting

The set of functions used for time series analysis and in forecasting.