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New Perspectives in Partial Least Squares and Related Methods
shares original, peer-reviewed research from presentations during
the 2012 partial least squares methods meeting (PLS 2012). This was
the 7th meeting in the series of PLS conferences and the first to
take place in the USA. PLS is an abbreviation for Partial Least
Squares and is also sometimes expanded as projection to latent
structures. This is an approach for modeling relations between data
matrices of different types of variables measured on the same set
of objects. The twenty-two papers in this volume, which include
three invited contributions from our keynote speakers, provide a
comprehensive overview of the current state of the most advanced
research related to PLS and related methods. Prominent scientists
from around the world took part in PLS 2012 and their contributions
covered the multiple dimensions of the partial least squares-based
methods. These exciting theoretical developments ranged from
partial least squares regression and correlation, component based
path modeling to regularized regression and subspace visualization.
In following the tradition of the six previous PLS meetings, these
contributions also included a large variety of PLS approaches such
as PLS metamodels, variable selection, sparse PLS regression,
distance based PLS, significance vs. reliability, and non-linear
PLS. Finally, these contributions applied PLS methods to data
originating from the traditional econometric/economic data to
genomics data, brain images, information systems, epidemiology, and
chemical spectroscopy. Such a broad and comprehensive volume will
also encourage new uses of PLS models in work by researchers and
students in many fields.
New Perspectives in Partial Least Squares and Related Methods
shares original, peer-reviewed research from presentations during
the 2012 partial least squares methods meeting (PLS 2012). This was
the 7th meeting in the series of PLS conferences and the first to
take place in the USA. PLS is an abbreviation for Partial Least
Squares and is also sometimes expanded as projection to latent
structures. This is an approach for modeling relations between data
matrices of different types of variables measured on the same set
of objects. The twenty-two papers in this volume, which include
three invited contributions from our keynote speakers, provide a
comprehensive overview of the current state of the most advanced
research related to PLS and related methods. Prominent scientists
from around the world took part in PLS 2012 and their contributions
covered the multiple dimensions of the partial least squares-based
methods. These exciting theoretical developments ranged from
partial least squares regression and correlation, component based
path modeling to regularized regression and subspace visualization.
In following the tradition of the six previous PLS meetings, these
contributions also included a large variety of PLS approaches such
as PLS metamodels, variable selection, sparse PLS regression,
distance based PLS, significance vs. reliability, and non-linear
PLS. Finally, these contributions applied PLS methods to data
originating from the traditional econometric/economic data to
genomics data, brain images, information systems, epidemiology, and
chemical spectroscopy. Such a broad and comprehensive volume will
also encourage new uses of PLS models in work by researchers and
students in many fields.
This handbook provides a comprehensive overview of Partial Least
Squares (PLS) methods with specific reference to their use in
marketing and with a discussion of the directions of current
research and perspectives. It covers the broad area of PLS methods,
from regression to structural equation modeling applications,
software and interpretation of results. The handbook serves both as
an introduction for those without prior knowledge of PLS and as a
comprehensive reference for researchers and practitioners
interested in the most recent advances in PLS methodology.
This handbook provides a comprehensive overview of Partial Least
Squares (PLS) methods with specific reference to their use in
marketing and with a discussion of the directions of current
research and perspectives. It covers the broad area of PLS methods,
from regression to structural equation modeling applications,
software and interpretation of results. The handbook serves both as
an introduction for those without prior knowledge of PLS and as a
comprehensive reference for researchers and practitioners
interested in the most recent advances in PLS methodology.
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