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crawl (version 1.3-2)

Fit continuous-time correlated random walk models for animal movement data

Description

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.

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Version

Install

install.packages('crawl')

Monthly Downloads

591

Version

1.3-2

License

Unlimited

Maintainer

Devin Johnson

Last Published

December 2nd, 2011

Functions in crawl (1.3-2)

-2 * log-likelihood for CTCRW models

Fit Continuous-Time Correlated Random Walk models to animal movement data

Create a weighted importance sample for posterior predictive track simulation.

Merge a location data set with a dry time (or other stopping) covariate

Fit Continuous-Time Correlated Random Walk Models to Animal Telemetry Data

Harbor seal relocation data set used in Johnson et al. (2008)

Simulate a value from the posterior distribution of a CTCRW model

northernFurSeal

Northern fur seal pup relocation data set used in Johnson et al. (2008)

Fill missing values in data set (or matrix) columns for which there is a single unique value

Expand a time indexed data set with additional prediction times

calculate estimate of log speed from a crwPredict object

Calculates AIC for all objects of class crwFit listed as arguments

Predict animal locations and velocities using a fitted CTCRW model and calculate measurement error fit statistics

'Flattening' a list-form crwPredict object into a data.frame

Compute a spatial use grid from a crawl prediction

Plot CRW predicted object

Reverse as.numeric command that is performed on a vector of type POSIXct

Construct a posterior simulation object for the CTCRW state vectors