In NMML/crawl: Fit Continuous-Time Correlated Random Walk Models to Animal Movement Data

knitr::opts_chunk$set(
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Correlated RAndom Walk Library of R functions

   

The [C]orrelated [RA]ndom [W]alk [L]ibrary of R functions was designed for fitting continuous-time correlated random walk (CTCRW) models with time indexed covariates. The model is fit using the Kalman-Filter on a state space version of the continuous-time stochastic movement process. The use case in the estimation of animal movement paths where the observed locations are determined from Argos or FastLoc enabled bio-loggers. In addition to the continuous-time component, {crawl} was specifically developed to incorporate the measurement error often associated with these observed locations. Lastly, {crawl} provides a framework for multiple imputation workflows for incorporation of model uncertainty.

The Future of crawl

The original code base and concepts for {crawl} were developed almost 15 years ago. Much has changed in the world of movement ecology, spatial statistics, R, bio-logging, and many other fields. In some cases, we've done a fairly good job keeping pace; in other cases, we've fallen behind. We feel it is time for a new approach and will, from now on, be focusing our development efforts on other packages and methods. We will continue to maintain {crawl}, improve the documentation, and ensure compatibility with dependent packages.

Installation

Install via CRAN

{crawl} is currently available on CRAN and R >= 4.0 is highly recommended.

# install latest version of crawl from CRAN
install.packages("crawl")

However, should {crawl} v 2.3.0 fail to pass CRAN checks it will be archived on CRAN and all future bug and check fixes will only be available on this repository and the R-universe repository described in the next section. So, if you cannot find {crawl} on CRAN, this has probably happened.

Install via R-Universe

The latest version of {crawl} is also available via R-Universe.

# Install crawl from my R-Universe repository
# Enable repository from dsjohnson

options(repos = c(
  dsjohnson = 'https://dsjohnson.r-universe.dev',
  CRAN = 'https://cloud.r-project.org'))

# Download and install crawl in R
install.packages('crawl')

# Browse the crawl manual pages
help(package = 'crawl')

You can also add the repository to your local list of repositories in your .Rprofile and this will ensure update.packages() pulls any new releases of {crawl} from R-Universe

#install.packages("usethis")
usethis::edit_r_profile()

# add the following text or replace existing repos option

options(repos = c(dsjohnson = 'https://dsjohnson.r-universe.dev',
                  CRAN = 'https://cloud.r-project.org'))

Install via Github

A development version of {crawl} is also available from GitHub. This version should be used with caution and only after consulting with package authors.

# install.packages("remotes")
remotes::install_github("NMML/crawl@devel")

Disclaimer

This repository is a scientific product and is not official communication of the National Oceanic and Atmospheric Administration, or the United States Department of Commerce. All NOAA GitHub project code is provided on an ‘as is’ basis and the user assumes responsibility for its use. NOAA and DOC have relinquished control of the information and no longer has responsibility to protect the integrity, confidentiality, or availability of the information. Any claims against the Department of Commerce or Department of Commerce bureaus stemming from the use of this GitHub project will be governed by all applicable Federal law. Any reference to specific commercial products, processes, or services by service mark, trademark, manufacturer, or otherwise, does not constitute or imply their endorsement, recommendation or favoring by the Department of Commerce. The Department of Commerce seal and logo, or the seal and logo of a DOC bureau, shall not be used in any manner to imply endorsement of any commercial product or activity by DOC or the United States Government.

NMML/crawl documentation built on Oct. 9, 2024, 11:56 a.m.