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smam (version 0.7.0)

Statistical Modeling of Animal Movements

Description

Animal movement models including Moving-Resting Process with Embedded Brownian Motion (Yan et al., 2014, ; Pozdnyakov et al., 2017, ), Brownian Motion with Measurement Error (Pozdnyakov et al., 2014, ), Moving-Resting-Handling Process with Embedded Brownian Motion (Pozdnyakov et al., 2020, ), Moving-Resting Process with Measurement Error (Hu et al., 2021, ), Moving-Moving Process with two Embedded Brownian Motions.

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Install

install.packages('smam')

Monthly Downloads

527

Version

0.7.0

License

GPL (>= 3.0)

Issues

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Maintainer

Chaoran Hu

Last Published

August 21st, 2023

Functions in smam (0.7.0)

transfData

Transfer raw dataset to the standard dataset (seasonal analysis toolbox)
rMR

Sampling from a Moving-Resting Process with Embedded Brownian Motion
integr.control

Auxiliary for Controlling Numerical Integration
rBMME

Sampling from Brown Motion with Measurement Error
rMRB

Sampling from a Moving-Resting bridge
vcov

Variance-Covariance Matrix of smam Estimators
rMRH

Sampling from a Moving-Resting-Handling Process with Embedded Brownian Motion
smam

smam: Statistical Modeling of Animal Movements
seasonFilter

Subsetting data during given season for each year (seasonal analysis toolbox)
approxNormalOrder

Auxiliary for Preparing Discrete Distribution used to approximating Standard Normal Distribution
fitMR

Fit a Moving-Resting Model with Embedded Brownian Motion
f109raw

GPS data of f109 (raw format)
fitMM

Fit a Moving-Moving Model with 2 Embedded Brownian Motion
fitBMME

Fit a Brownian Motion with Measurement Error
dtm

Density for Time Spent in Moving or Resting
fitMRH

Fit a Moving-Resting-Handling Model with Embedded Brownian Motion
estVarMRME_Godambe

Variance matrix of estimators from moving-resting process with measurement error
estimate

Estimate Result of smam Estimators
rMM

Sampling from a Moving-Moving Process with 2 Embedded Brownian Motion
f109

GPS data of f109
fitStateMRH

Estimation of states at each time point with Moving-Resting-Handling Process
fitMRME

Fit a Moving-Resting Model with Measurement Error
rBB

Sampling from a Brownian bridge path give a grid time
fitStateMR

Estimation of states at each time point with Moving-Resting Process