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Simple linear regression with multiple level shifts
Author(s) -
Lu Qiqi,
Lund Robert B.
Publication year - 2007
Publication title -
canadian journal of statistics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.804
H-Index - 51
eISSN - 1708-945X
pISSN - 0319-5724
DOI - 10.1002/cjs.5550350308
Subject(s) - estimator , simple linear regression , asymptotic distribution , simple (philosophy) , mathematics , ordinary least squares , consistency (knowledge bases) , statistics , linear regression , strong consistency , series (stratigraphy) , linear model , generalized least squares , general linear model , regression analysis , discrete mathematics , paleontology , biology , philosophy , epistemology
The authors study the properties of the ordinary least squares trend estimator in a simple linear regression model with multiple known level shift times. The error component in the model is taken to be a general short‐memory stationary time series. The authors establish the consistency and asymptotic normality of the estimator. They also present a climatological application in which the multiple level shifts are prominent features.