Optimization methods in time series interpolation

Abstract

The problem of estimating missing observations in time series with a known model is studied. An approach based directly on the minimization of a suitable criterion holding the residuals as free variables is discussed. The optimization problem can be solved by methods of nonlinear optimization, and utilizing its special structure. The method may also be utilized under various constraints set on the variables. Explicit algorithms based on the method are given and demonstrated to produce accurate results

Keywords:

• missing observations
• interpolation
• algorithms
• nonlinear optimization
• time series
• ARIMA models