Also, this paper has some example R code (in Ecological Archives) to
simulate a track from bivariate random walk.

@ARTICLE{patterson2010using,
  author = {Patterson, T.A. and McConnell, B.J. and Fedak, M.A. and
Bravington,
 M.V. and Hindell, M.A.},
  title = {{Using GPS data to evaluate the accuracy of state-space methods
for
 correction of Argos satellite telemetry error}},
  journal = {Ecology},
  year = {2010},
  volume = {91},
  pages = {273--285},
  number = {1},
  publisher = {Eco Soc America}
}

I'm not sure if the supplement is availalbe publicly, but if not and you
don't have access you could perhaps email the author:

http://www.esapubs.org/archive/ecol/E091/020/suppl-1.htm#anchorFilelist

Cheers, Mike.
On Sat, Oct 2, 2010 at 12:44 PM, Michael Sumner <mdsumner@gmail.com> wrote:

> There's an example in the trip package function filter.penSS that might be
> of interest, provided by my supervisor Simon Wotherspoon. You could adjust
> the values to get 30 min intervals.
>
>  ## Fake some data
>
>      ## Brownian motion tethered at each end
>      brownian.bridge <- function(n, r) {
>        x <- cumsum(rnorm(n, 0, 1))
>        x <- x - (x[1] + seq(0, 1, length = n) * (x[n] - x[1]))
>        r * x
>      }
>
>      ## Number of days and number of obs
>      days <- 50
>      n <- 200
>
>      ## Make separation between obs gamma distributed
>      x <- rgamma(n, 3)
>      x <- cumsum(x)
>      x <- x/x[n]
>
>      ## Track is lissajous + brownian bridge
>      b.scale <- 0.6
>      r.scale <- sample(c(0.1, 2, 10.2), n, replace = TRUE, prob = c(0.8,
> 0.18, 0.02))
>      set.seed(44)
>
>      tms <- ISOdate(2001, 1, 1) + trunc(days * 24 * 60 * 60 *x)
>      lon <- 120 + 20 * sin(2 * pi * x) + brownian.bridge(n, b.scale) +
> rnorm(n, 0, r.scale)
>      lat <- -40 + 10 *(sin(3 * 2 * pi * x) + cos(2 * pi * x) - 1) +
> brownian.bridge(n, b.scale) + rnorm(n, 0, r.scale)
>
>      tr <- new("trip", SpatialPointsDataFrame(cbind(lon, lat),
> data.frame(gmt = tms, id = "lbb")), TimeOrderedRecords(c("gmt", "id")))
>
>   On Sat, Oct 2, 2010 at 7:30 AM, Andy Bunn <Andy.Bunn@wwu.edu> wrote:
>
>> > -----Original Message-----
>> > From: r-sig-geo-bounces@stat.math.ethz.ch [mailto:r-sig-geo-
>> > bounces@stat.math.ethz.ch] On Behalf Of Roberto Badilla Fuentes
>> > Sent: Friday, October 01, 2010 12:42 PM
>> > To: r-sig-geo
>> > Subject: [R-sig-Geo] Random Movement Generator
>> >
>> > Hi All,
>> >
>> > Is there a functionality in R that allows for the creation of random
>> > path or
>> > trajectory?  Probably Brownian Motion can help but I'd like to output
>> > the
>> > data points and be able to have the points separated, say every 30
>> > minutes.
>>
>> I've used like this before in class to teach about random walks. Maybe
>> this will get you going? HTH, Andy
>>
>> require(sp)
>> xinit <- 0
>> yinit <- 0
>> d2move <- 1
>> nsteps <- 99
>> x <- c(xinit,rep(NA,nsteps))
>> y <- c(yinit,rep(NA,nsteps))
>> for(i in 2:(nsteps+1)){
>>  theta <- runif(1,pi/180,360*pi/180)
>>  xi <- d2move * cos(theta)
>>  yi <- d2move * sin(theta)
>>  x[i] <- x[i-1] + xi
>>  y[i] <- y[i-1] + yi
>> }
>> plot(x,y,type='b')
>> xy <- SpatialPoints(cbind(x,y))
>> str(xy)
>>
>>
>>
>>
>>
>>
>> >
>> >
>> > I also tried BM{sde}.  Is there a way plot the points generated?
>> >
>> > Thanks in advance
>> > Roberto
>> >
>> >       [[alternative HTML version deleted]]
>> >
>> > _______________________________________________
>> > R-sig-Geo mailing list
>> > R-sig-Geo@stat.math.ethz.ch
>> > https://stat.ethz.ch/mailman/listinfo/r-sig-geo
>>
>> _______________________________________________
>> R-sig-Geo mailing list
>> R-sig-Geo@stat.math.ethz.ch
>> https://stat.ethz.ch/mailman/listinfo/r-sig-geo
>>
>
>
>
> --
> Michael Sumner
> Institute for Marine and Antarctic Studies, University of Tasmania
> Hobart, Australia
> e-mail: mdsumner@gmail.com
>



-- 
Michael Sumner
Institute for Marine and Antarctic Studies, University of Tasmania
Hobart, Australia
e-mail: mdsumner@gmail.com

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