Statistics, Department of
The R Journal
Date of this Version
6-2012
Document Type
Article
Citation
The R Journal (June 2012) 4(1)
Abstract
MARSS is a package for fitting multivariate autoregressive state-space models to time-series data. The MARSS package implements state-space models in a maximum likelihood framework. The core functionality of MARSSis based on likelihood maximization using the Kalman filter/smoother, combined with an EM algorithm. To make comparisons with other packages available, parameter estimation is also permitted via direct search routines avail able in ’optim’. The MARSS package allows data to contain missing values and allows a wide variety of model structures and constraints to be specified (such as fixed or shared parameters). In addition to model-fitting, the package provides bootstrap routines for simulating data and generating confidence intervals, and multiple options for calculating model selection criteria (such as AIC).
Included in
Numerical Analysis and Scientific Computing Commons, Programming Languages and Compilers Commons
Comments
Copyright 2012, The R Foundation. Open access material. License: CC BY 3.0 Unported