Behavioral state |
A discrete (and typically latent) behavior associated with a specific type of movement. |
Behavior; behavioral mode |
Brownian motion |
A simple random walk in continuous time, i.e., a diffusion model with no centralizing tendency. |
Wiener process |
Central tendency |
A tendency to move back towards a central location (e.g., the center of a home range or patch) as a result of directed movement. |
Mean-reverting |
Correlated movement |
Short-term directional persistence resulting from a tendency to continue moving in a similar direction (or velocity) as previous moves. |
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Directed movement |
Systematic, non-random movement in a particular direction. Directed movement associated with a particular location or gradient, such as a “center of attraction,” can result in long-term directional persistence and/or central tendency. |
Biased or oriented movement (discrete time); drift or advection (continuous time) |
Directional persistence |
A tendency for successive movements to be in a similar direction. |
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Hidden Markov model |
A special class of state-space models with a finite number of hidden (e.g., behavioral) states. |
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Markov process |
A stochastic process where state transitions are dependent only on the current state (first-order Markov process) or current and immediately previous states (higher-order Markov process). |
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Multistate model |
A mixture of random walk models corresponding to different movement behavior states. |
Mixture model, switching model |
Ornstein-Uhlenbeck (OU) process |
A diffusion model with centralizing tendency that accounts for dependence between observations. With no central tendency, Brownian motion is obtained as a limiting case. |
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Random walk |
Given an initial starting position, a mathematical model for generating a stochastic movement trajectory in space. Random walks are often Markov processes and can be formulated in discrete or continuous time. They have no directional persistence or bias. |
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State-space model |
A conditionally specified hierarchical model consisting of a latent system process model and an observation model. |
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