Multiple Unobserved Sources of Error State Space Models R package muse version 0.1.1 CRAN Task View: TimeSeries (https://CRAN.R-project.org/view=TimeSeries) 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) <doi:10.1017/CBO9781107049994>, Durbin and Koopman (2012) <doi:10.1093/acprof:oso/9780199641178.001.0001>, Proietti (2000) <doi:10.1016/S0169-2070(00)00037-6>, Sbrana and Silvestrini (2023) <doi:10.1016/j.ijforecast.2022.03.003> 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. Software Depends: R (>= 3.0.2), greybox, smooth Imports: Rcpp (>= 0.12.3), generics (>= 0.1.2), zoo LinkingTo: Rcpp, RcppArmadillo (>= 0.8.100.0.0) Suggests: testthat (>= 3.0.0), knitr, rmarkdown Ivan Svetunkov <ivan@svetunkov.com> Comprehensive R Archive Network (CRAN) Diego J. Pedregal [aut, ctb] (ORCID: <https://orcid.org/0000-0003-4958-0969>), Ivan Svetunkov [aut, cre] (Senior Lecturer at Centre for Marketing Analytics and Forecasting, Lancaster University, UK, ORCID: <https://orcid.org/0000-0001-7826-0281>) LGPL-2.1 2026-07-30 application/tgz https://CRAN.R-project.org/package=muse doi:10.32614/CRAN.package.muse en-GB