simm.kf: Simulate KF

In galuardi/SatTagSim: Simulation from Electronic Tags

Description

Correlated random walk simluator based on advection diffusion process equation

Usage

simm.kf(
  n = 100,
  u = c(0, 1),
  v = c(0, 1),
  D = c(100, 50),
  sp = c(-70, 40),
  ulim = c(-50, 50),
  vlim = c(-50, 50),
  Dlim = c(0, 5000)
)

Arguments

n	number of points to simulate
u	vector of mean and standard deviation of advection in u (longitude) direction, in nautical miles/day
v	vector of mean and standard deviation of advection in v (latitude) direction, in nautical miles/day
D	vector of mean and standard deviation of Diffusion, in nautical miles^2/day
sp	vector of starting point (lon, lat)

Details

uses truncated normal distributions. Bounds are:

Parameter	lower bound	upper bound
u	-50	50
v	-50	50
D	0	5000

Value

a two column matrix of longitude and latitude

Author(s)

Benjamin Galuardi

References

Sibert, J. R., Musyl, M. K. and Brill, R. W. 2003. Horizontal movements of bigeye tuna (Thunnus obesus) near Hawaii determined by Kalman filter analysis of archival tagging data. Fish. Oceanogr. 12(3): 141?151. Calenge, C. (2006) The package adehabitat for the R software: a tool for the analysis of space and habitat use by animals. Ecological Modelling, 197, 516-519

See Also

make.sim.track.par

Examples

# Three examples of differing advection and Diffusion parameter combinations
par(mfrow=c(1,3))
plot(simm.kf(n = 1000, u = c(5,1), v = c(5,1), D = c(10,1), sp = c(-70,40)), typ = 'o', pch = 19, col =2, xlab = 'lon', ylab = 'lat')
plot(simm.kf(n = 1000, u = c(10,1), v = c(0,1), D = c(10,1), sp = c(-70,40)), typ = 'o', pch = 19, col =3, xlab = 'lon', ylab = 'lat')
plot(simm.kf(n = 1000, u = c(0,0), v = c(0,0), D = c(5000,1000), sp = c(-70,40)), typ = 'o', pch = 19, col =4, xlab = 'lon', ylab = 'lat')

galuardi/SatTagSim documentation built on Nov. 15, 2020, 6:28 a.m.