Handbook of Computational Econometrics examines the state of
the art of computational econometrics and provides exemplary
studies dealing with computational issues arising from a wide
spectrum of econometric fields including such topics as
bootstrapping, the evaluation of econometric software, and
algorithms for control, optimization, and estimation. Each topic is
fully introduced before proceeding to a more in-depth examination
of the relevant methodologies and valuable illustrations.
This book:
Provides self-contained treatments of issues in computational
econometrics with illustrations and invaluable bibliographies.
Brings together contributions from leading researchers.
Develops the techniques needed to carry out computational
econometrics.
Features network studies, non-parametric estimation,
optimization techniques, Bayesian estimation and inference, testing
methods, time-series analysis, linear and nonlinear methods, VAR
analysis, bootstrapping developments, signal extraction, software
history and evaluation.
This book will appeal to econometricians, financial
statisticians, econometric researchers and students of econometrics
at both graduate and advanced undergraduate levels.
Handbook of Computational Econometrics
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Handbook of Computational Econometrics examines the state of
the art of computational econometrics and provides exemplary
studies dealing with computational issues arising from a wide
spectrum of econometric fields including such topics as
bootstrapping, the evaluation of econometric software, and
algorithms for control, optimization, and estimation. Each topic is
fully introduced before proceeding to a more in-depth examination
of the relevant methodologies and valuable illustrations.
This book:
Provides self-contained treatments of issues in computational
econometrics with illustrations and invaluable bibliographies.
Brings together contributions from leading researchers.
Develops the techniques needed to carry out computational
econometrics.
Features network studies, non-parametric estimation,
optimization techniques, Bayesian estimation and inference, testing
methods, time-series analysis, linear and nonlinear methods, VAR
analysis, bootstrapping developments, signal extraction, software
history and evaluation.
This book will appeal to econometricians, financial
statisticians, econometric researchers and students of econometrics
at both graduate and advanced undergraduate levels.