crw: Simulate a correlated random walk

In jsta/glatos: A package for the Great Lakes Acoustic Telemetry Observation System

Simulate a correlated random walk

Description

Simulate a random walk as series of equal-length steps with turning angles drawn from a normal distribution.

Usage

crw(theta = c(0, 5), stepLen = 10, initPos = c(0, 0),
  initHeading = 0, nsteps = 10000)

Arguments

theta	A 2-element numeric vector with turn angle parameters (theta[1] = mean; theta[2] = sd) from normal distribution.
stepLen	A numeric scalar with total distance moved in each step.
initPos	A 2-element numeric vector with nital position (initPos[1]=x, initPos[2]=y).
initHeading	A numeric scalar with initial heading in degrees.
nsteps	A numeric scalar with number of steps to simulate.

Details

First, nsteps turn angles are drawn from a normal distribution. Second, the cumulative sum of the vector of turn angles defines the heading within each step. The x and y component vectors in each are then calculated and summed to obtain the simualted path.

Value

A two-column data frame containing:

x	x coordinates
y	y coordinates

Note

Adapted from code provided by Tom Binder.

Author(s)

C. Holbrook ([e-mail])

Examples

foo <- crw(theta=c(0,5), stepLen=10, initPos=c(0,0), initHeading=0, 
  nsteps=10)
plot(foo,type="o",pch=20,asp=c(1,1))

jsta/glatos documentation built on July 11, 2022, 7:01 a.m.