Minimum distance estimation and goodness-of-fit tests in first-order autoregression
Consider the first-order autoregressive model \(X_ i=\rho X_{i- 1}+\epsilon_ i\), where the \(\{\epsilon_ i\}\) are i.i.d. according to a df F, symmetric about zero. The paper considers a minimum distance estimator of \(\rho\), within a certain class determined by a finite measure on the Borel line. In this class an asymptotically efficient estimator is exhibited. The paper also discusses goodness-of-fit tests of symmetry and for a specified error distribution.
scientific article; zbMATH DE number 3982343