Data.COST {COST} | R Documentation |
Data Generation
Description
Generating data from COST DGP, assuming Markov process of order one
Usage
Data.COST(n,n.total,seed1,coord,par.t)
Arguments
n |
number of time points for parameter estimation |
n.total |
number of total time points, with a burning sequence |
seed1 |
random seed to generate a data set, for reproducibility |
coord |
coordinates of the locations |
par.t |
the true copula parameters |
Value
Y.all |
data from all locations and time points, may include data at time point n+1, or data from new locations |
mean.true |
true conditional mean of observed locations at time point n+1 |
Author(s)
Yanlin Tang, Huixia Judy Wang
References
Yanlin Tang, Huixia Judy Wang, Ying Sun, Amanda Hering. Copula-based semiparametric models for spatio-temporal data.
Examples
library(COST)
n = 500
n.total = 1001
seed1 = 22222
coord = cbind(rep(c(1,3,5)/6,each=3),rep(c(1,3,5)/6,3))
par.t = c(0,1,1,0.5,1.5,100)
dat = Data.COST(n,n.total,seed1,coord,par.t)
#it returns a data set with dimension 501*9
[Package COST version 0.1.0 Index]