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Classification and Data Analysis
International Federation of Classification Societies The International Federation of Classification Societies (IFCS) is an agency for the dissemination of technical and scientific information concerning classification and data analysis in the broad sense and in as wide a· range of applications as possible; founded in 1985 in Cambridge (UK) from the following Scientific Societies and Groups: British Classification Society -BCS; Classification Society of North America -CSNA; Gesellschaft fUr Klassifikation -GfKl; Japanese Classification Society -JCS; Classification Group of Italian Statistical Society - COSIS; Societe Francophone de Classification -SFC. Now the IFCS includes the following Soc...
Graphical Models for Categorical Data
For advanced students of network data science, this compact account covers both well-established methodology and the theory of models recently introduced in the graphical model literature. It focuses on the discrete case where all variables involved are categorical and, in this context, it achieves a unified presentation of classical and recent results.
Handbook of Graphical Models
A graphical model is a statistical model that is represented by a graph. The factorization properties underlying graphical models facilitate tractable computation with multivariate distributions, making the models a valuable tool with a plethora of applications. Furthermore, directed graphical models allow intuitive causal interpretations and have become a cornerstone for causal inference. While there exist a number of excellent books on graphical models, the field has grown so much that individual authors can hardly cover its entire scope. Moreover, the field is interdisciplinary by nature. Through chapters by leading researchers from different areas, this handbook provides a broad and acce...
Bayesian Statistics 9
The Valencia International Meetings on Bayesian Statistics - established in 1979 and held every four years - have been the forum for a definitive overview of current concerns and activities in Bayesian statistics. These are the edited Proceedings of the Ninth meeting, and contain the invited papers each followed by their discussion and a rejoinder by the authors(s). In the tradition of the earlier editions, this encompasses an enormous range of theoretical and applied research, high lighting the breadth, vitality and impact of Bayesian thinking in interdisciplinary research across many fields as well as the corresponding growth and vitality of core theory and methodology. The Valencia 9 invi...
Algebraic Methods in Statistics and Probability II
A decade after the publication of Contemporary Mathematics Vol. 287, the present volume demonstrates the consolidation of important areas, such as algebraic statistics, computational commutative algebra, and deeper aspects of graphical models. --
High Confidence Network Predictions from Big Biological Data
Biology functions in a most intriguing fashion, with human cells being regulated by multiplex networks of proteins and their dependent systems that control everything from proliferation to cell death. Notably, there are cases when these networks fail to function properly. In some diseases there are multiple small perturbations that push the otherwise healthy cells into a state of malfunction. These maladies are referred to as complex diseases, and include common disorders such as allergy, diabetes type II, and multiple sclerosis, and due to their complexity there is no universally defined approach to fully understand their pathogenesis or pathophysiology. While these perturbations can be mea...
Mathematical Reviews
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Current Index to Statistics, Applications, Methods and Theory
The Current Index to Statistics (CIS) is a bibliographic index of publications in statistics, probability, and related fields.
Topics at the Frontier of Statistics and Network Analysis
This snapshot of the current frontier of statistics and network analysis focuses on the foundational topics of modeling, sampling, and design. Primarily for graduate students and researchers in statistics and closely related fields, emphasis is not only on what has been done, but on what remains to be done.
