Shrinkage estimation for linear regression with ARMA errors
R Wu, Q Wang - Journal of Statistical Planning and Inference, 2012 - Elsevier
In this paper, we extend the modified lasso of Wang et al.(2007) to the linear regression
model with autoregressive moving average (ARMA) errors. Such an extension is far from
trivial because new devices need to be called for to establish the asymptotics due to the
existence of the moving average component. A shrinkage procedure is proposed to
simultaneously estimate the parameters and select the informative variables in the
regression, autoregressive, and moving average components. We show that the resulting …
model with autoregressive moving average (ARMA) errors. Such an extension is far from
trivial because new devices need to be called for to establish the asymptotics due to the
existence of the moving average component. A shrinkage procedure is proposed to
simultaneously estimate the parameters and select the informative variables in the
regression, autoregressive, and moving average components. We show that the resulting …
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