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Titlebook: Estimating and Choosing; An Essay on Probabil Georges Matheron Book 1989 Springer-Verlag Berlin Heidelberg 1989 construction.modeling.proba

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书目名称Estimating and Choosing
副标题An Essay on Probabil
编辑Georges Matheron
视频video
图书封面Titlebook: Estimating and Choosing; An Essay on Probabil Georges Matheron Book 1989 Springer-Verlag Berlin Heidelberg 1989 construction.modeling.proba
描述Ever since the beginning of modern probability theory in the seventeenth century there has been a continuous debate over the meaning and applicability of the concept of probability. This book presents a coherent and well thoughtout framework for the use of probabilistic models to describe unique phenomena in a purely objective way. Although .Estimating and. .Choosing. was written with geostatistical applications in mind, the approach is of general applicability across the whole spectrum of probabilistic modelling. The only full-fledged treatment of the foundations of practical probability modelling ever written, this book fills an important gap in the literature of probability and statistics.
出版日期Book 1989
关键词construction; modeling; probability; probability theory; statistics
版次1
doihttps://doi.org/10.1007/978-3-642-48817-7
isbn_softcover978-3-540-50087-2
isbn_ebook978-3-642-48817-7
copyrightSpringer-Verlag Berlin Heidelberg 1989
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Global Modelsl particular cases, without even claiming in any way that the procedure I shall follow (namely going through the intermediary of “probabilistic representations”) is the only possible one, or even necessarily the best.
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Book 1989l applicability across the whole spectrum of probabilistic modelling. The only full-fledged treatment of the foundations of practical probability modelling ever written, this book fills an important gap in the literature of probability and statistics.
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Book 1989 of the concept of probability. This book presents a coherent and well thoughtout framework for the use of probabilistic models to describe unique phenomena in a purely objective way. Although .Estimating and. .Choosing. was written with geostatistical applications in mind, the approach is of genera
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