Regression Analysis Under A Priori Parameter Restrictions

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Springer Science & Business Media, Sep 28, 2011 - Business & Economics - 234 pages
This monograph focuses on the construction of regression models with linear and non-linear constrain inequalities from the theoretical point of view. Unlike previous publications, this volume analyses the properties of regression with inequality constrains, investigating the flexibility of inequality constrains and their ability to adapt in the presence of additional a priori information The implementation of inequality constrains improves the accuracy of models, and decreases the likelihood of errors. Based on the obtained theoretical results, a computational technique for estimation and prognostication problems is suggested. This approach lends itself to numerous applications in various practical problems, several of which are discussed in detail The book is useful resource for graduate students, PhD students, as well as for researchers who specialize in applied statistics and optimization. This book may also be useful to specialists in other branches of applied mathematics, technology, econometrics and finance
 

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Contents

Estimation of Regression Model Parameterswith Specific Constraints
1
Asymptotic Properties of Parameters in Nonlinear Regression Models
29
Method of Empirical Means in Nonlinear Regression and Stochastic Optimization Models
73
Determination of Accuracy of Estimation of Regression Parameters Under Inequality Constraints
121
Asymptotic Properties of Recurrent Estimates of Parameters of Nonlinear Regression with Constraints
182
Prediction of Linear Regression Evaluated Subject to Inequality Constraints on Parameters
211
Bibliographic Remarks
223
References
226
Index
233
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