isleRoyal

<p>Example data set for estimation of species interaction strengths. These are data on the number of wolves and 
  moose on Isle Royal, Michigan.  The data are unlogged.  The covariate data are the average Jan-Feb, average Apr-May and average July-Sept
  temperature (Fahrenheit) and precipitation (inches).  Also included are 3-year running means of these covariates.  The choice of 
  covariates is based on those presented in the Isle Royale 2012 annual report.</p>

datasets

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/>.

Elizabeth Holmes  NOAA Federal

MARSS

Multivariate Autoregressive State-Space Modeling

Elizabeth Eli Holmes

Eric J. Ward

Mark D. Scheuerell

Kellie Wills

isleRoyal function

<p>The data are supplied as a matrix with years in the first column.</p>

Format

Isle Royale Wolf and Moose Data — isleRoyal

Isle Royale Wolf and Moose Data

isleRoyal: Isle Royale Wolf and Moose Data

Description

Usage

Arguments

Format

Examples