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MARSS

Multivariate Autoregressive State-Space Modeling

v3.11.10 · Sep 10, 2025 · GPL-2

Description

The MARSS package provides maximum-likelihood parameter estimation for constrained and unconstrained linear multivariate autoregressive state-space (MARSS) models, including partially deterministic models. MARSS models are a class of dynamic linear model (DLM) and vector autoregressive model (VAR) model. Fitting available via Expectation-Maximization (EM), BFGS (using optim), and 'TMB' (using the 'marssTMB' companion package). Functions are provided for parametric and innovations bootstrapping, Kalman filtering and smoothing, model selection criteria including bootstrap AICb, confidences intervals via the Hessian approximation or bootstrapping, and all conditional residual types. See the user guide for examples of dynamic factor analysis, dynamic linear models, outlier and shock detection, and multivariate AR-p models. Online workshops (lectures, eBook, and computer labs) at <https://atsa-es.github.io/>.

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NOTE 11 OK · 3 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE Mar 10, 2026
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package dependencies

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Dependencies Reverse dependencies generics KFAS mvtnorm nlme dsem estar freqdom MARSS

Version History

new 3.11.10 Mar 10, 2026
updated 3.11.10 ← 3.11.9 diff Sep 9, 2025
updated 3.11.9 ← 3.11.8 diff Feb 18, 2024
updated 3.11.8 ← 3.11.4 diff May 19, 2023
updated 3.11.4 ← 3.11.3 diff Dec 14, 2021
updated 3.11.3 ← 3.11.1 diff Oct 20, 2020
updated 3.11.1 ← 3.10.12 diff Aug 26, 2020
updated 3.10.12 ← 3.10.10 diff Feb 3, 2020
updated 3.10.10 ← 3.10.8 diff Nov 1, 2018
updated 3.10.8 ← 3.9 diff Apr 13, 2018
updated 3.9 ← 3.8 diff Mar 20, 2014
updated 3.8 ← 3.7 diff Mar 17, 2014
updated 3.7 ← 3.6 diff Dec 13, 2013
updated 3.6 ← 3.5 diff Nov 25, 2013
updated 3.5 ← 3.4 diff Oct 22, 2013
updated 3.4 ← 3.3 diff Feb 17, 2013
updated 3.3 ← 3.2 diff Jan 25, 2013
updated 3.2 ← 3.1 diff Aug 29, 2012
updated 3.1 ← 2.9 diff Jul 12, 2012
updated 2.9 ← 2.8 diff May 29, 2012