Improvement in Modified Least Squares Estimation for Fitting a Sinusoidal Regression Model with AR (1) Error
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Abstract
Sinusoidal functions are widely used in many areas, such as physics, engineering, and gene expression to describe correlated data along with time. A sinusoidal model with correlated error is fitted using a modified two-stage least squares method by modifying the weight matrix of the correlation coefficient based on residuals from the one-way ANOVA model proposed by Pukdee, Polsen, and Baksh (2020). By using that modification, a conditional least squares model with the AR (1) error is modified and proposed as an alternative method. A Monte Caro simulation study is made of an effect of error mis-specifications and this finding might be beneficial for some applications.
Keywords: autoregressive process, conditional least squares, one-way ANOVA model
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