openforecast-org.r-universe.dev

[openforecast-org] smooth 4.5.0

ivan@svetunkov.com (Ivan Svetunkov) — Fri, 17 Jul 2026 09:07:53 GMT

Functions implementing Single Source of Error state space models for purposes of time series analysis and forecasting. The package includes ADAM (Svetunkov, 2023, ), Exponential Smoothing (Hyndman et al., 2008, ), SARIMA (Svetunkov & Boylan, 2019 ), Complex Exponential Smoothing (Svetunkov & Kourentzes, 2018, ), Simple Moving Average (Svetunkov & Petropoulos, 2018 ) and several simulation functions. It also allows dealing with intermittent demand based on the iETS framework (Svetunkov & Boylan, 2019, ).

[openforecast-org] muse 0.1.0

ivan@svetunkov.com (Ivan Svetunkov) — Wed, 08 Jul 2026 08:54:26 GMT

Implements the Power / Trend / Seasonal (PTS) model, a unified state-space framework based on the Multiple Source of Error (MSOE) model. It brings the trend, seasonal and irregular component models of Harvey (1989) , Durbin and Koopman (2012) , Proietti (2000) , Sbrana and Silvestrini (2023) and others together under a single estimation, selection and forecasting interface, with an optional Box-Cox power transformation. Models are estimated by maximum likelihood through the Kalman filter and smoother, with automatic component selection by information criteria.

[openforecast-org] greybox 2.0.9

ivan@svetunkov.com (Ivan Svetunkov) — Mon, 29 Jun 2026 16:16:05 GMT

Implements functions and instruments for regression model building and its application to forecasting. The main scope of the package is in variables selection and models specification for cases of time series data. This includes promotional modelling, selection between different dynamic regressions with non-standard distributions of errors, selection based on cross validation, solutions to the fat regression model problem and more. Models developed in the package are tailored specifically for forecasting purposes. So as a results there are several methods that allow producing forecasts from these models and visualising them.

[openforecast-org] legion 0.2.2.41003

ivan@svetunkov.com (Ivan Svetunkov) — Fri, 21 Nov 2025 10:52:22 GMT

Functions implementing multivariate state space models for purposes of time series analysis and forecasting. The focus of the package is on multivariate models, such as Vector Exponential Smoothing, Vector ETS (Error-Trend-Seasonal model) etc. It currently includes Vector Exponential Smoothing (VES, de Silva et al., 2010, ), Vector ETS (Svetunkov et al., 2023, ) and simulation function for VES.