Description Usage Arguments Examples
timixCov function is a mixed model function to solve synchronized time sereis. The effects of synchronization and serial correlation are treated as the random effects. The variance-covariance matrix of random effects are prescribed by the parameters rho and omega. timixCov function estimate these two parameters through oprimization.
1 |
dat |
data for the analysis |
y |
column number of the dependent variable |
f |
column number of the fixed effects |
r |
column number of the random effects |
grp |
column number of the group |
1 2 3 4 5 6 7 8 9 | n_time <- 50
n_grp <- 5
y <- simuOneCol(n_time, n_grp, rho = 0.5, omega = 0.5, mean = 0)
x0 <- rep(1, n_time * n_grp) # Intercept
x1 <- simuOneCol(n_time, n_grp, rho = 0.5, omega = 1, mean = 0)
x2 <- simuOneCol(n_time, n_grp, rho = 0.5, omega = 0, mean = 0)
area <- makeGrp(n_time, n_grp)
dat <- data.frame(y, x0, x1, x2, area)
res <- timixCov(dat, y = 1, f = 2:4, r = 2:4, grp = 5)
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