Estimation of the parameters in a simple state space via the EM algorithm.
EM0(num, y, A, mu0, Sigma0, Phi, cQ, cR, max.iter = 50, tol = 0.01)number of observations
observation vector or time series
time-invariant observation matrix
initial state mean vector
initial state covariance matrix
state transition matrix
Cholesky-like decomposition of state error covariance matrix Q -- see details below
Cholesky-like decomposition of state error covariance matrix R -- see details below
maximum number of iterations
relative tolerance for determining convergence
Estimate of Phi
Estimate of Q
Estimate of R
Estimate of initial state mean
Estimate of initial state covariance matrix
-log likelihood at each iteration
number of iterations to convergence
relative tolerance at convergence
Practically, the script only requires that Q or R may be reconstructed as
t(cQ)%*%(cQ) or t(cR)%*%(cR), respectively.