rBMME {smam} | R Documentation |
Sampling from Brown Motion with Measurement Error
Description
Given the volatility parameters of a Brownian motion and normally distributed measurement errors, generate the process at discretely observed time points of a given dimension.
Usage
rBMME(time, dim = 2, sigma = 1, delta = 1)
rBmme(time, dim = 2, sigma = 1, delta = 1)
Arguments
time |
vector of time points at which observations are to be sampled |
dim |
(integer) dimension of the Brownian motion |
sigma |
volatility parameter (sd) of the Brownian motion |
delta |
sd parameter of measurement error |
Value
A data.frame
whose first column is the time points and whose
other columns are coordinates of the locations.
References
Pozdnyakov V., Meyer, TH., Wang, Y., and Yan, J. (2013) On modeling animal movements using Brownian motion with measurement error. Ecology 95(2): p247–253. doi:doi:10.1890/13-0532.1.
Examples
tgrid <- seq(0, 10, length = 1001)
## make it irregularly spaced
tgrid <- sort(sample(tgrid, 800))
dat <- rBMME(tgrid, 1, 1)
plot(dat[,1], dat[,2], xlab="t", ylab="X(t)", type="l")
[Package smam version 0.7.2 Index]