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Decision Processes by Using Bivariate Normal Quantile Pairs (Hardcover, 1st ed. 2015)
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Decision Processes by Using Bivariate Normal Quantile Pairs (Hardcover, 1st ed. 2015)
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This book discusses equi-quantile values and their use in
generating decision alternatives under the twofold complexities of
uncertainty and dependence, offering scope for surrogating between
two alternative portfolios when they are correlated. The book
begins with a discussion on components of rationality and learning
models as indispensable concepts in decision-making processes. It
identifies three-fold complexities in such processes: uncertainty,
dependence and dynamism. The book is a novel attempt to seek
tangible solutions for such decision problems. To do so, four
hundred tables of bi-quantile pairs are presented for carefully
chosen grids. In fact, it is a two-variable generalization of the
inverse normal integral table, which is used in obtaining bivariate
normal quantile pairs for the given values of probability and
correlation. When making decisions, only two of them have to be
taken at a time. These tables are essential tools for
decision-making under risk and dependence, and offer scope for
delving up to a single step of dynamism. The book subsequently
addresses averments dealing with applications and advantages. The
content is useful to empirical scientists and risk-oriented
decision makers who are often required to make choices on the basis
of pairs of variables. The book also helps simulators seeking valid
confidence intervals for their estimates, and particle physicists
looking for condensed confidence intervals for Higgs-Boson
utilizing the Bose-Einstein correlation given the magnitude of such
correlations. Entrepreneurs and investors as well as students of
management, statistics, economics and econometrics, psychology,
psychometrics and psychographics, social sciences, geographic
information system, geology, agricultural and veterinary sciences,
medical sciences and diagnostics, and remote sensing will also find
the book very useful.
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