Simulated time series data for a deterministic linear damped oscillator model
The variables are as follows:
data(LinearOsc)
A data frame with 1000 rows and 3 variables
ID. ID of the systems (1 to 10)
x. Latent level variable
theTimes. Measured time Points
# The following was used to generate the data #-------------------------------------- ## Not run: Osc <- function(t, prevState, parms) { x1 <- prevState[1] # x1[t] x2 <- prevState[2] # x2[t] eta1 = parms[1] zeta1 = parms[2] with(as.list(parms), { dx1 <- x2 dx2 <- eta1*x1 + zeta1*x2 res<-c(dx1,dx2) list(res) } ) } n = 10 #Number of subjects T = 100 #Number of time points deltaT = .1 #dt lastT = deltaT*T #Value of t_{i,T} theTimes = seq(0, lastT, length=T) #A list of time values eta = -.8 zeta = -.1 out1 = matrix(NA,T*n,1) trueOut = matrix(NA,T*n,1) parms = c(eta, zeta) for (i in 1:n){ xstart = c(rnorm(1,0,2),rnorm(1,0,.5)) out <- lsoda(as.numeric(xstart), theTimes, Osc, parms) trueOut[(1+(i-1)*T):(i*T)] = out[,2] out1[(1+(i-1)*T):(i*T)] = out[,2]+rnorm(T,0,1) } LinearOsc= data.frame(ID=rep(1:n,each=T),x=out1[,1], theTimes=rep(theTimes,n)) save(LinearOsc,file="LinearOsc.rda") ## End(Not run)
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