(Received August 1, 1991; revised April 28, 1992)
Abstract. A state-space model to perform discrete thin plate smoothing for data on a two-dimensional rectangular lattice is proposed with the use of the Kalman filter. The use of the Kalman filter reduces computational difficulties in the maximum likelihood estimation of a smoothing parameter. A procedure to reduce computational difficulties in the estimation of trend is given also. Numerical illustration is provided using two sets of artificial data.
Key words and phrases: Discrete thin plate smoothing, image analysis, Kalman filter, likelihood, spatial statistics, state-space approach.