MARSS - Multivariate Autoregressive State-Space Modeling
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/>.
Last updated
multivariate-timeseriesstate-space-modelsstatisticstime-series
10.67 score 54 stars 3 dependents 1.1k scripts 1.2k downloadsbayesdfa - Bayesian Dynamic Factor Analysis (DFA) with 'Stan'
Implements Bayesian dynamic factor analysis with 'Stan'. Dynamic factor analysis is a dimension reduction tool for multivariate time series. 'bayesdfa' extends conventional dynamic factor models in several ways. First, extreme events may be estimated in the latent trend by modeling process error with a student-t distribution. Second, alternative constraints (including proportions are allowed). Third, the estimated dynamic factors can be analyzed with hidden Markov models to evaluate support for latent regimes.
Last updated
onetbbcpp
8.01 score 29 stars 126 scripts 699 downloadsmaxnet - Fitting 'Maxent' Species Distribution Models with 'glmnet'
Procedures to fit species distributions models from occurrence records and environmental variables, using 'glmnet' for model fitting. Model structure is the same as for the 'Maxent' Java package, version 3.4.0, with the same feature types and regularization options. See the 'Maxent' website <http://biodiversityinformatics.amnh.org/open_source/maxent> for more details.
Last updated
6.45 score 10 dependents 307 scripts 6.1k downloadstvvarss - Time Varying Vector Autoregressive State Space Models
The tvvarss package uses Stan (mc-stan.org) to fit multi-site multivariate autoregressive (aka vector autoregressive) state space models with a time varying interaction matrix.
Last updated
bayesianmultivariate-timeseriesstate-spacetime-seriesonetbbcpp
4.08 score 12 stars 6 scriptsmarssTMB - Fast fitting of MARSS models with TMB
Companion to the MARSS package. Fast fitting of MARSS models with TMB. See the MARSS documentation. All the model syntax and features are the same as for the MARSS package.
Last updated
marssmultivariate-timeseriesstate-space-modeltime-seriestmb
4.00 score 1 stars 40 scriptsmvdlm - Multivariate Dynamic Linear Modelling With Stan
Fits multivariate dynamic linear models in a Bayesian framework using Stan.
Last updated
bayesiandlmstantime-seriesonetbbcpp
2.70 score 1 stars 3 scripts
MAR1 - Multivariate Autoregressive Modeling for Analysis of Community Time-Series Data
The MAR1 package provides basic tools for preparing ecological community time-series data for MAR modeling, building MAR-1 models via model selection and bootstrapping, and visualizing and exporting model results. It is intended to make MAR analysis sensu Ives et al. (2003) Analysis of community stability and ecological interactions from time-series data) a more accessible tool for anyone studying community dynamics. The user need not necessarily be familiar with time-series modeling or command-based statistics programs such as R.
Last updated
multivariate-timeseriestime-series
3.00 score 1 stars 7 downloadsvarlasso - Vector Autoregressive State Space Models With Shrinkage
The varlasso package uses Stan (mc-stan.org) to fit VAR state space models with optional shrinkage priors on B matrix elements (autoregression coefficients).
Last updated
bayesianmultivariate-timeseriestime-seriesonetbbcpp
3.00 score 2 stars 2 scripts