Analysis method for linear regression model with unequally spaced autoregression series error

The analysis method for regression model with unequally spaced time series error is presented, which is based on the relationship between the Green function of continuous system and the autoregression parameters of the time series. The conditional maximum likelihood estimation and exact maximum likelihood estimation of parameters of the regression model with unequally spaced correlated error are discussed in detail. The method is not only suitable for the time series with missing observations but also applicable to the irregularly sampled data in social and natural science. The method can also combine regression with autoregression and promote the precision of analysis and forecast. Numerical examples are given at last, which can illustrate the performance of the new method.