In the summer of 1970, Georges Matheron, the father of geostatistics, presented a series of lectures at the Centre de Morphologie Mathmatique in France. These lectures would go on to become Matheron's Theory of Regionalized Variables, a seminal work that would inspire hundreds of papers and become the bedrock of numerous theses and books on the topic; however, despite their importance, the notes were never formally published. In this volume, Matheron's influential work is presented as a published book for the first time. Originally translated into English by Charles Huijbregts, and carefully curated here, this book stays faithful to Matheron's original notes. The text has been ordered with a common structure, and equations and figures have been redrawn and numbered sequentially for ease of reference. While not containing any mathematical technicalities or case studies, the reader is invited to wonder about the physical meaning of the notions Matheron deals with. When Matheron wrote them, he considered the theory of linear geostatistics complete and the book his final one on the subject; however, this end for Matheron has been the starting point for most geostatisticians.

'Geostatistical Analysis of Compositional Data' provides a comprehensive coverage of the theory and practice of analysis of data that have both spatial and compositional dependence, characteristics of most earth science and environmental measurements.

Modeling and Analysis of Compositional Data presents a practical and comprehensive introduction to the analysis of compositional data along with numerous examples to illustrate both theory and application of each method. Based upon short courses delivered by the authors, it provides a complete and current compendium of fundamental to advanced methodologies along with exercises at the end of each chapter to improve understanding, as well as data and a solutions manual which is available on an accompanying website. Complementing Pawlowsky-Glahn s earlier collective text that provides an overview of the state-of-the-art in this field, Modeling and Analysis of Compositional Data fills a gap in the literature for a much-needed manual for teaching, self learning or consulting.