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The bias of the least squares estimator over interval constraints
Authors:Luis A. Escobar
Affiliation:1. Jiangsu Collaborative Innovation Center on Atmospheric Environment and Equipment Technology, Nanjing University of Information Science and Technology, Nanjing 210044, China;2. State Key Laboratory of Severe Weather, Chinese Academy of Meteorological Sciences, Beijing 100081, China;3. Jiangsu Key Laboratory of Big Data Analysis Technology, Nanjing University of Information Science and Technology, Nanjing 210044, China;1. Maisonneuve-Rosemont Research Center, Montreal, Quebec, Canada;2. Department of Microbiology, Infectiology and Immunology, University of Montreal, Montreal, Quebec, Canada;1. Department of Aerospace Engineering, Tohoku University, Sendai, 980-8579 Japan;2. Department of Mechanical Engineering, Kyushu Sangyo University, Fukuoka 813-8503 Japan;1. Institute of Fundamental Technological Research, Warsaw, Poland;2. Institute of Mechanized Construction and Rock Mining, Warsaw, Poland;1. College of Computer Science, Zhejiang University, China;2. Department of Applied Mathematics, University of Twente, Netherlands
Abstract:We show that the interval constrained least squares estimator for a regression model is in general bias. The bias and some of its properties are given when the regression residuals are normally distributed.
Keywords:
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