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PUBLICATIONS

Reconstruction of Conditional Expectations from Product Moments with Applications

Published

Author(s)

Robert C. Hagwood

Abstract

Regression calibration is a method for fitting models when the independent variable X is measured with error. In regression calibration, the noisy independent measurement W for X is calibrated with E[X | W] and the model is fitted using whatever method is appropriate using this replacement for X. An important component of this approach is using the data to find a good estimator of E[X | W]. In this paper, the function E[X | W = w] is estimated using the classical moment problem.
Citation
Journal of Computational and Applied Mathematics
Volume
276
Pub Type
Journals

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Keywords

calibration, regression calibration, moment problem, Vandermonde.
Statistical analysis

Citation

Hagwood, R. (2015), Reconstruction of Conditional Expectations from Product Moments with Applications, Journal of Computational and Applied Mathematics, [online], https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=908278 (Accessed April 19, 2024)

Created April 9, 2015, Updated January 27, 2020