EAN: 9784431557838

SPRINGERBRIEFS IN STATISTICS STATISTICAL CAUS...

This is the first book to provide a comprehensive introduction to a new semiparametric causal
discovery approach known as LiNGAM  with the fundamental background needed to understand it. It
offers a general overview of the basics of the LiNGAM approach for causal discovery  estimation
principles  and algorithms. This semiparametric approach is one of the most exciting new topics
in the field of causal discovery. The new framework assumes parametric assumptions on the
functional forms of structural equations but makes no assumption on the distributions of
exogenous variables other than non-Gaussianity. It provides data-analysis tools capable of
estimating a much wider class of causal relations even in the presence of hidden common causes.
This feature is in contrast to conventional nonparametric approaches based on conditional
independence of variables. This book is highly recommended to readers who seek an in-depth and
up-to-date overview of this new causal discovery approach to advance the technique as well as
to those who are interested in applying this approach to real-world problems. This LiNGAM
approach should become a standard item in the toolbox of statisticians  machine learners  and
practitioners who need to perform observational studies.

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