Description Usage Arguments Value Author(s) References Examples
Simulate data from our Bayesian melding model with Brownian Bridge and Brownian Motion (See the model description in BMAnimalTrack
).
1 2 |
T |
Number of time points in the animal's path and DR path. |
K |
Number of GPS observations. |
s2H |
Variance parameter for Brownian Bridge. |
s2D |
Variance parameter for the Brownian motion. |
s2G |
Variance of the measurement error in the GPS observations. |
gind |
Optional. The time points where the GPS observations are obtained. Default is randomly generating from 1:T. |
betaVec |
Coefficients in the function h(t). When unspecified, no parametric bias term is considered. |
dMx |
Design matrix of dimension T. Default the polynomials. |
A |
Start point of the path. Default 0. |
B |
End point of the path. Default 0. |
scale |
Logical (TRUE of FALSE). Whether to standardize the columns of |
A data list with the following elements:
eta |
The simulated path of the animal, |
Y |
The GPS observations, |
Ytime |
The time points where the GPS observations are available, |
X |
Dead-Reckoned path |
Yang (Seagle) Liu <yang.liu@stat.ubc.ca>
Liu, Y., Battaile, B. C., Zidek, J. V., and Trites, A. (2014). Bayesian melding of the Dead-Reckoned path and gps measurements for an accurate and high-resolution path of marine mammals. arXiv preprint arXiv: 1411.6683.
1 2 3 4 5 6 7 8 | set.seed(1)
#Generating data from our
dlist <- dataSim(T=100, K=10, s2H=1, s2D=0.1, betaVec=c(1))
gpsObs <- dlist$Y
gpsTime <- dlist$Ytime
drPath <- dlist$X
wlist <- as.dataList(drPath, gpsObs, gpsTime, timeUnit=1, s2G=0.01, dUnit=1, betaOrder=1)
##Examples continues in function "as.dataList".
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