Title

The Pattern of R-Square in Linear Regression Model with First-Order Autoregressive Error Process and Bayesian property: Computer Simulation

Authors

• Mei-Yu Lee, Department of Applied Financial Management, Yuanpei University, Taiwan

Journal name

Journal of Accounting Finance & Management Strategy (ABI)

Abstract

This paper provides a basic investigation of an R-square and sum-square error (SSE) in a linear regression model with the errors following a first-order autoregressive process in which the autocorrelation coefficients are non-zero. The consideration and measurement of the model are difficult to control, thus a computer stimulation is necessary to corroborate how the R-square and SSE are affected by the autocorrelation coefficients. The evidence reveals that the R-square and SSE differ in the ranges of positive and negative autocorrelation coefficients. The results show that it would require one to verify the estimators including the R-square or SSE for testing non-zero autocorrelation coefficients.

Keywords

Autocorrelation Coefficient, First-order Autoregressive Process, R-square, Computer Simulation

Citation

Mei-Yu Lee, 2014, The Pattern of R-Square in Linear Regression Model with First-Order Autoregressive Error Process and Bayesian property: Computer Simulation, Journal of Accounting Finance & Management Strategy, 9(1), 115-132.

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link

Recommended citation: Mei-Yu Lee, 2014, The Pattern of R-Square in Linear Regression Model with First-Order Autoregressive Error Process and Bayesian property: Computer Simulation, " Journal of Accounting Finance & Management Strategy, 9(1), 115-132.