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The Complete Convergence for the Parameter Estimator of the First-Order Autoregressive Process Created by WOD Errors
Abstract
The autoregressive process play an important role in predicting problems leading to decision making. In practise, to estimate the unknown parameter V of the autoregressive model we use the least square method. We already saw that the least squares estimator V_n complete converge to unknown parameter V of the first-order autoregressive process generated by extended negatively dependent errors. In this paper, we examine the complete convergence
of the estimator #n also under widely orthant dependent errors and we construct exponential inequalities of the coefficient of 1st order autoregressive model which enable us to build a confidence interval.
Keywords
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