Estimation in multiple linear regression Berkson model for processes with uncorrelated increments |
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Authors: | Tiee-Jian Wu Huang-Yu Chen |
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Affiliation: | Department of Statistics, National Cheng-Kung University, Tainan, 70101 Taiwan, ROC |
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Abstract: | This paper presents a method of estimating the regression and variance parameters in the multiple linear regression Berkson model for a continuous-time stochastic process with uncorrelated increments. Under minimal conditions, we establish (i) the Gauss–Markov theorem and the quadratic mean—as well as the strong consistency of the proposed estimate of the regression parameter and (ii) the weak consistency of the proposed estimate of the variance parameter. |
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Keywords: | Continuous-time linear regression Gauss&ndash Markov theorem Measurement error Processes with uncorrelated increments |
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