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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/>.

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multivariate-timeseriesstate-space-modelsstatisticstime-series

10.64 score 54 stars 3 dependents 792 scripts 1.5k downloads

bayesdfa - 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.

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cpp

7.94 score 29 stars 103 scripts 1.0k downloads

maxnet - 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.

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6.48 score 10 dependents 262 scripts 7.7k downloads

atsar - Stan Routines For Univariate And Multivariate Time Series

Bundles univariate and multivariate STAN scripts for FISH 507 class.

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bayesianstantime-seriescpp

5.98 score 48 stars 67 scripts

tvvarss - 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.

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bayesianmultivariate-timeseriesstate-spacetime-seriescpp

4.26 score 12 stars 15 scripts

marssTMB - 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.

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marssmultivariate-timeseriesstate-space-modeltime-seriestmb

3.98 score 1 stars 38 scripts

atsalibrary - Packages, data and scripts for ATSA course and lab book

This package will load the needed packages and data files for the ATSA course material when students install.

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3.19 score 4 stars 78 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.

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multivariate-timeseriestime-series

3.00 score 1 stars 4 downloads

varlasso - 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).

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bayesianmultivariate-timeseriestime-seriescpp

3.00 score 2 stars 2 scripts

mvdlm - Multivariate Dynamic Linear Modelling With Stan

Fits multivariate dynamic linear models in a Bayesian framework using Stan.

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bayesiandlmstantime-seriescpp

2.70 score 1 stars 3 scripts