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Combinatorial Inference in Geometric Data Analysis

of points. Combinatorial Inference in Geometric Data Analysis gives an overview of multidimensional statistical inference methods applicable to;

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Combinatorial Inference in Geometric Data Analysis

of points. Combinatorial Inference in Geometric Data Analysis gives an overview of multidimensional statistical inference methods applicable to;

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Geometric and Topological Inference

field of topological data analysis. Building on a rigorous treatment of simplicial complexes and distance functions, this self-contained book;

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Geometric and Topological Inference

field of topological data analysis. Building on a rigorous treatment of simplicial complexes and distance functions, this self-contained book;

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Combinatorial Maps

A Versatile Framework for Handling Subdivided Geometric Objects Combinatorial Maps: Efficient Data Structures for Computer Graphics;

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Combinatorial Maps

A Versatile Framework for Handling Subdivided Geometric Objects Combinatorial Maps: Efficient Data Structures for Computer Graphics;

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Big Data in Omics and Imaging: Integrated Analysis and Causal Inference

Big Data in Omics and Imaging: Integrated Analysis and Causal Inference addresses the recent development of integrated genomic, epigenomic;

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Big Data in Omics and Imaging: Integrated Analysis and Causal Inference

Big Data in Omics and Imaging: Integrated Analysis and Causal Inference addresses the recent development of integrated genomic, epigenomic;

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Combinatorial Optimization and Applications

submissions. The papers are organized in topical sections such as graph theory, geometric optimization, complexity and data structure, combinatorial;

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Maximum Entropy and Bayesian Methods

focused on time series analysis, machine learning, deformable geometric models, and data analysis of Monte Carlo simulations, as well as reviewing;

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Discrete Geometry for Computer Imagery

are organized in topical sections on Models for Discrete Geometry, Discrete and Combinatorial Topology, Geometric Transforms, Discrete Shape;

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Discrete Geometry for Computer Imagery

topology; shape descriptors; models for discrete geometry; circle drawing; morphological analysis; geometric transforms; and discrete shape;

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Exact Statistical Inference for Categorical Data

time. In addition to the existing conditional exact inference, some efficient, unconditional exact approaches could be used in data analysis to;

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Combinatorial Geometry

A complete, self-contained introduction to a powerful and resurging mathematical discipline . Combinatorial Geometry presents and explains;

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Mathematical Sciences Research Institute Publications

arrangements, polytopes, packing, covering, discrete convexity, geometric algorithms and their complexity, and the combinatorial complexity;

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Mathematical Sciences Research Institute Publications

arrangements, polytopes, packing, covering, discrete convexity, geometric algorithms and their complexity, and the combinatorial complexity;

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Big Data in Omics and Imaging, Two Volume Set

analysis and the modern advanced statistical methods for big data Provides tools for high dimensional data reduction Discusses searching;

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Combinatorial Reciprocity Theorems

Combinatorial reciprocity is a very interesting phenomenon, which can be described as follows: A polynomial, whose values at positive;

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Davenport-Schinzel Sequences and their Geometric Applications

These sequences exhibit some surprising properties that make them a fascinating subject for research in combinatorial analysis. This 1995;

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Davenport-Schinzel Sequences and their Geometric Applications

These sequences exhibit some surprising properties that make them a fascinating subject for research in combinatorial analysis. This 1995;

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Combinatorial Optimization and Applications

submissions. Topics covered include classic combinatorial optimization; geometric optimization; network optimization; applied optimization;

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Handbook Of Applied Econometrics And Statistical Inference

Summarizing developments and techniques in the field, this reference covers sample surveys, nonparametric analysis, hypothesis testing;

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Handbook Of Applied Econometrics And Statistical Inference

Summarizing developments and techniques in the field, this reference covers sample surveys, nonparametric analysis, hypothesis testing;

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Statistics And Data Analysis

more modern ideas of data analysis. The book is divided into three parts. Part One is concerned with data in general and with describing groups;

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Inference for Heavy-Tailed Data

scattered in different statistics journals. Inference for Heavy-Tailed Data Analysis puts these methods into a single place with a clear picture on;

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Time Series

undergraduate and M.S. students. Basic theoretical results are presented in a mathematically convincing way, and the methods of data analysis are;

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Time Series

undergraduate and M.S. students. Basic theoretical results are presented in a mathematically convincing way, and the methods of data analysis are;

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