# NOT RUN {
# Generates 500 observations from a linear state space model with
# (phi, sigma_e, sigma_v) = (0.5, 1.0, 0.1) and zero initial state.
theta <- c(0.5, 1.0, 0.1)
d <- generateData(theta, noObservations=500, initialState=0.0)
# Estimate the filtered state using Kalman filter
kfOutput <- kalmanFilter(d$y, theta,
initialState=0.0, initialStateCovariance=0.01)
# Plot the estimate and the true state
par(mfrow=c(3, 1))
plot(d$x, type="l", xlab="time", ylab="true state", bty="n",
col="#1B9E77")
plot(kfOutput$xHatFiltered, type="l", xlab="time",
ylab="Kalman filter estimate", bty="n", col="#D95F02")
plot(d$x-kfOutput$xHatFiltered, type="l", xlab="time",
ylab="difference", bty="n", col="#7570B3")
# }
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