Animal Movement Modelling using Hidden Markov Models
Confidence intervals for angle parameters
Confidence intervals
Exponential density function
Gamma density function
Log-normal density function
Von Mises density function
Weibull density function
Wrapped Cauchy density function
Example data simulation
Fit an HMM to the data
Discrete colour palette for states
Data to produce plots of fitted model
Is moveData
Is moveHMM
Forward log-probabilities
Backward log-probabilities
Constructor of moveData objects
Constructor of moveHMM objects
Plot moveHMM
Plot pseudo-residuals
Pseudo-residuals
Simulation tool
Split track at gaps
State probabilities
Stationary state probabilities
Summary moveData
Transition probability matrix
Turning angle
Viterbi algorithm
Matrix of all probabilities
AIC
Scaling function: natural to working parameters.
Negative log-likelihood
Negative log-likelihood function
Parameters definition
Plot moveData
Plot observations on satellite image
Plot states
Plot stationary state probabilities
Predict stationary state probabilities
Predict transition probabilities for new covariate values
Preprocessing of the tracking data
Print moveHMM
Scaling function: working to natural parameters
Provides tools for animal movement modelling using hidden Markov models. These include processing of tracking data, fitting hidden Markov models to movement data, visualization of data and fitted model, decoding of the state process, etc. <doi:10.1111/2041-210X.12578>.