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Much of what is said about yoga is misleading. To take two
examples, it is neither five thousand years old, as is commonly
claimed, nor does it mean union, at least not exclusively. In
perhaps the most famous text-The Yoga Sutras of Patanjali-the aim
is separation, isolating consciousness from everything else. And
the earliest evidence of practice dates back about twenty-five
hundred years. Yoga may well be older, but no one can prove it.
Scholars have learned a lot more about the history of yoga in
recent years, but their research can be hard to track down.
Although their work is insightful, it is aimed more at specialists
than at general readers. Daniel Simpson's The Truth of Yoga draws
on many of their findings, presented in a format designed for
practitioners. The aim is to highlight ideas on which readers can
draw to keep traditions alive in the twenty-first century. It
offers an overview of yoga's evolution from its earliest origins to
the present. It can either be read chronologically or be used as a
reference guide to history and philosophy. Each short section
addresses one element, quoting from traditional texts and putting
their teachings into context. The intention is to keep things clear
without oversimplifying.
This book offers the first in-depth enquiry into the origins of 135
Indigenous Australian objects acquired by the Royal Navy between
1795 and 1855 and held now by the British Museum. In response to
increasing calls for the 'decolonisation' of museums and the
restitution of ethnographic collections, the book seeks to return
knowledge of the moments, methods, and motivations whereby
Indigenous Australian objects were first collected and sent to
Britain. By structuring its discussion in terms of three key
'stages' of a typical naval voyage to Australia-departure from
British shores, arrival on the continent's coasts, and eventual
return to port-the book offers a nuanced and multifaceted
understanding of the pathways followed by these 135 objects into
the British Museum. The book offers important new understandings of
Indigenous Australian peoples' reactions to naval visitors, and
contains a wealth of original research on the provenance and
meaning of some of the world's oldest extant Indigenous Australian
object collections.
Modeling spatial and spatio-temporal continuous processes is an
important and challenging problem in spatial statistics. Advanced
Spatial Modeling with Stochastic Partial Differential Equations
Using R and INLA describes in detail the stochastic partial
differential equations (SPDE) approach for modeling continuous
spatial processes with a Matern covariance, which has been
implemented using the integrated nested Laplace approximation
(INLA) in the R-INLA package. Key concepts about modeling spatial
processes and the SPDE approach are explained with examples using
simulated data and real applications. This book has been authored
by leading experts in spatial statistics, including the main
developers of the INLA and SPDE methodologies and the R-INLA
package. It also includes a wide range of applications: * Spatial
and spatio-temporal models for continuous outcomes * Analysis of
spatial and spatio-temporal point patterns * Coregionalization
spatial and spatio-temporal models * Measurement error spatial
models * Modeling preferential sampling * Spatial and
spatio-temporal models with physical barriers * Survival analysis
with spatial effects * Dynamic space-time regression * Spatial and
spatio-temporal models for extremes * Hurdle models with spatial
effects * Penalized Complexity priors for spatial models All the
examples in the book are fully reproducible. Further information
about this book, as well as the R code and datasets used, is
available from the book website at http://www.r-inla.org/spde-book.
The tools described in this book will be useful to researchers in
many fields such as biostatistics, spatial statistics,
environmental sciences, epidemiology, ecology and others. Graduate
and Ph.D. students will also find this book and associated files a
valuable resource to learn INLA and the SPDE approach for spatial
modeling.
This book offers the first in-depth enquiry into the origins of 135
Indigenous Australian objects acquired by the Royal Navy between
1795 and 1855 and held now by the British Museum. In response to
increasing calls for the 'decolonisation' of museums and the
restitution of ethnographic collections, the book seeks to return
knowledge of the moments, methods, and motivations whereby
Indigenous Australian objects were first collected and sent to
Britain. By structuring its discussion in terms of three key
'stages' of a typical naval voyage to Australia-departure from
British shores, arrival on the continent's coasts, and eventual
return to port-the book offers a nuanced and multifaceted
understanding of the pathways followed by these 135 objects into
the British Museum. The book offers important new understandings of
Indigenous Australian peoples' reactions to naval visitors, and
contains a wealth of original research on the provenance and
meaning of some of the world's oldest extant Indigenous Australian
object collections.
Modeling spatial and spatio-temporal continuous processes is an
important and challenging problem in spatial statistics. Advanced
Spatial Modeling with Stochastic Partial Differential Equations
Using R and INLA describes in detail the stochastic partial
differential equations (SPDE) approach for modeling continuous
spatial processes with a Matern covariance, which has been
implemented using the integrated nested Laplace approximation
(INLA) in the R-INLA package. Key concepts about modeling spatial
processes and the SPDE approach are explained with examples using
simulated data and real applications. This book has been authored
by leading experts in spatial statistics, including the main
developers of the INLA and SPDE methodologies and the R-INLA
package. It also includes a wide range of applications: * Spatial
and spatio-temporal models for continuous outcomes * Analysis of
spatial and spatio-temporal point patterns * Coregionalization
spatial and spatio-temporal models * Measurement error spatial
models * Modeling preferential sampling * Spatial and
spatio-temporal models with physical barriers * Survival analysis
with spatial effects * Dynamic space-time regression * Spatial and
spatio-temporal models for extremes * Hurdle models with spatial
effects * Penalized Complexity priors for spatial models All the
examples in the book are fully reproducible. Further information
about this book, as well as the R code and datasets used, is
available from the book website at http://www.r-inla.org/spde-book.
The tools described in this book will be useful to researchers in
many fields such as biostatistics, spatial statistics,
environmental sciences, epidemiology, ecology and others. Graduate
and Ph.D. students will also find this book and associated files a
valuable resource to learn INLA and the SPDE approach for spatial
modeling.
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