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adehabitat (version 1.8.20)

simm.mou: Simulation of a Bivariate Ornstein-Uhlenbeck Process

Description

This function simulates a bivariate Ornstein-Uhlenbeck process for animal movement.

Usage

simm.mou(date = 1:100, b = c(0, 0),
         a = diag(0.5, 2), x0 = b,
         sigma = diag(2), id = "A1",
         burst = id)

Arguments

date

a vector indicating the date (in seconds) at which relocations should be simulated. This vector can be of class POSIXct

b

a vector of length 2 containing the coordinates of the attraction point

a

a 2*2 matrix

x0

a vector of length 2 containing the coordinates of the startpoint of the trajectory

sigma

a 2*2 positive definite matrix

id

a character string indicating the identity of the simulated animal (see help(ltraj))

burst

a character string indicating the identity of the simulated burst (see help(ltraj))

Value

An object of class ltraj

Details

The Ornstein-Uhlenbeck process can be used to take into account an "attraction point" into the animal movements (Dunn and Gipson 1977). This process can be simulated using the stochastic differential equation: $$d\mathbf{z} = \mathbf{a} ( \mathbf{b} - \mathbf{z}(t)) dt + \mathbf{\Sigma} d \mathbf{B2(t)}$$ The vector b contains the coordinates of the attraction point. The matrix a (2 rows and 2 columns) contains coefficients controlling the force of the attraction. The matrix Sigma controls the noise added to the movement (see ?simm.mba for details on this matrix).

References

Dunn, J.E., & Gipson, P.S. (1977) Analysis of radio telemetry data in studies of home range. Biometrics 33: 85--101.

See Also

simm.brown, ltraj, simm.crw, simm.mba

Examples

Run this code
# NOT RUN {
set.seed(253)
u <- simm.mou(1:50, burst="Start at the attraction point")
v <- simm.mou(1:50, x0=c(-3,3),
              burst="Start elsewhere")
w <- simm.mou(1:50, a=diag(c(0.5,0.1)), x0=c(-3,3),
              burst="Variable attraction")
x <- simm.mou(1:50, a=diag(c(0.1,0.5)), x0=c(-3,7),
              burst="Both")
z <- c(u,v,w,x)

plot(z, addpoints = FALSE, perani = FALSE)

# }

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