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