Linear regression under multiple changepoints
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This dissertation studies the least squares estimator of a trend parameter in a simple linear regression model with multiple changepoints when the changepoint times are known. The error component in the model is allowed to be autocorrelated. The least squares estimator of the trend and the variance of the trend estimator are derived. Consistency and asymptotic normality of the trend estimator are established under wide generality. The Lund et al. (2001) temperature trend study of the contiguous 48 United States is updated as an application.