:: Volume 16, Issue 1 (9-2022) ::
JSS 2022, 16(1): 127-148 Back to browse issues page
Modified Two-Stage Sampling Around the Mean of the First-Order Autoregressive Model
Eisa Mahmoudi * , Soudabeh Sajjadipanah , Mohammad Sadegh Zamani
Abstract:   (1882 Views)
In this paper, a modified two-stage procedure in the Autoregressive model  AR(1) is considered, which investigates the point and the interval estimation of the mean based on the least-squares estimator. The modified two-stage procedure is as effective as the best fixed-sample size procedure. In this regard, the significant properties of the procedure, including asymptotic risk efficiency, first-order efficiency, consistent, and asymptotic distribution of the mean, are established. Then, a Monte Carlo simulation study is deduced to investigate the modified two-stage procedure. The performance of estimators and confidence intervals are evaluated utilizing a simulation study. Finally, real-time series data is considered to illustrate the applicability of the modified two-stage procedure.
Keywords: Modified Two-Stage Procedure, Autoregressive Model, Least-Squares Estimator, Monte Carlo Simulation.
Full-Text [PDF 336 kb]   (1204 Downloads)    
Type of Study: Research | Subject: Time Series
Received: 2021/10/19 | Accepted: 2022/09/1 | Published: 2022/08/2



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Volume 16, Issue 1 (9-2022) Back to browse issues page