A proposed conditional method for estimating ARMA(1, 1) model

Document Type : Research Paper

Author

Department of Statistics, College of Administration and Economic, Baghdad University, Iraq.

Abstract

This paper aims to study the parameters estimation methods of the stationary mixed model  (autoregressive-moving average) of low order ARMA (1, 1) regarding to time domain analysis in univariate time series. Using the approximating methods: Back Forecasting (BF), Classical Conditional Maximum Likelihood (CC) and Proposed Conditional Maximum Likelihood(PC). A comparison is done among the three methods by Mean Squared Error (MSE) using several simulation experiments; the obtained results from the empirical analysis indicate that the accuracy of the proposed conditional method is better than the classical conditional method.

Keywords

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Volume 13, Issue 1
March 2022
Pages 3011-3020
  • Receive Date: 13 May 2021
  • Accept Date: 06 October 2021