ISOLATING CYCLICAL PATTERNS IN IRREGULAR TIME-SERIES DATA

Times-series data which are observed at irregular time intervals often arise in economics and the bio-sciences. Existing methods for modelli ng these data have focused on the discretisation of continuous process es. A method is proposed for fitting cyclical components to irregular time-series data based on the continuous-discrete Kalman filter which incorporates numerical integration of the differential equations descr ibing the model. The method is applied to seawater temperature data an d empirical sampling distributions for parameter estimators are enumer ated. The supporting sampling distributions suggest that the method yi elds estimates which have satisfactory statistical properties.