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Modeling patterns in data using linear and related models
Author(s) -
Maxwell Engelhardt
Publication year - 1996
Publication title -
osti oai (u.s. department of energy office of scientific and technical information)
Language(s) - English
Resource type - Reports
DOI - 10.2172/266746
Subject(s) - covariate , linear model , linear regression , generalized linear model , proper linear model , estimator , general linear model , computer science , reliability (semiconductor) , regression analysis , data mining , econometrics , statistics , mathematics , power (physics) , polynomial regression , quantum mechanics , physics
This report considers the use of linear models for analyzing data related to reliability and safety issues of the type usually associated with nuclear power plants. The report discusses some of the general results of linear regression analysis, such as the model assumptions and properties of the estimators of the parameters. The results are motivated with examples of operational data. Results about the important case of a linear regression model with one covariate are covered in detail. This case includes analysis of time trends. The analysis is applied with two different sets of time trend data. Diagnostic procedures and tests for the adequacy of the model are discussed. Some related methods such as weighted regression and nonlinear models are also considered. A discussion of the general linear model is also included. Appendix A gives some basic SAS programs and outputs for some of the analyses discussed in the body of the report. Appendix B is a review of some of the matrix theoretic results which are useful in the development of linear models

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