Scan Statistics [electronic resource] : Methods and Applications / edited by Joseph Glaz, Vladimir Pozdnyakov, Sylvan Wallenstein.

Contributor(s): Glaz, Joseph [editor.] | Pozdnyakov, Vladimir [editor.] | Wallenstein, Sylvan [editor.] | SpringerLink (Online service)
Material type: TextTextSeries: Statistics for Industry and Technology: Publisher: Boston, MA : Birkhäuser Boston, 2009Description: XXVIII, 394 p. 40 illus. online resourceContent type: text Media type: computer Carrier type: online resourceISBN: 9780817647490Subject(s): Statistics | Mathematical statistics | Applied mathematics | Engineering mathematics | Probabilities | Biomathematics | Statistics | Statistical Theory and Methods | Statistics for Life Sciences, Medicine, Health Sciences | Probability Theory and Stochastic Processes | Physiological, Cellular and Medical Topics | Probability and Statistics in Computer Science | Applications of MathematicsAdditional physical formats: Printed edition:: No titleDDC classification: 519.5 LOC classification: QA276-280Online resources: Click here to access online
Contents:
Joseph Naus: Father of the Scan Statistic -- Precedence-Type Tests for the Comparison of Treatments with a Control -- Extreme Value Results for Scan Statistics -- Boundary Crossing Probability Computationsin the Analysis of Scan Statistics -- Approximations for Two-Dimensional Variable Window Scan Statistics -- Applications of Spatial Scan Statistics: A Review -- Extensions of the Scan Statistic for the Detection and Inference of SpatialClusters -- 1-Dependent Stationary Sequences and Applications to Scan Statistics -- Scan Statistics in Genome-Wide Scan for Complex Trait Loci -- On Probabilities for Complex Switching Rules in Sampling Inspection -- Bayesian Network Scan Statistics for Multivariate Pattern Detection -- ULS Scan Statistic for Hotspot Detection with Continuous Gamma Response -- False Discovery Control for Scan Clustering -- Martingale Methods for Patterns and Scan Statistics -- How Can Pattern Statistics Be Useful for DNA Motif Discovery? -- Occurrence of Patterns and Motifs in Random Strings -- Detection of Disease Clustering.
In: Springer eBooksSummary: Scan statistics is currently one of the most active and important areas of research in applied probability and statistics, having applications to a wide variety of fields: archaeology, astronomy, bioinformatics, biosurveillance, molecular biology, genetics, computer science, electrical engineering, geography, material sciences, physics, reconnaissance, reliability and quality control, telecommunication, and epidemiology. Filling a gap in the literature, this self-contained volume brings together a collection of selected chapters illustrating the depth and diversity of theory, methods and applications in the area of scan statistics. Key features: * Chapters are written by leading experts in the field. * Features many current results and highlights new directions for future research. * Includes challenging theoretical methodological research problems. * Presentation is accessible to statisticians as well as to scientists from other disciplines where scan statistics are employed. * Real-world applications to areas such as bioinformatics and biosurveillance are emphasized. * Contains extensive references to research articles, books, and relevant computer software. Scan Statistics is an excellent reference for graduate students and researchers in applied probability and statistics, as well as for scientists in biology, computer science, pharmaceutical science, medicine, geography, quality control, communications, and epidemiology. The work may also be used as a textbook for a graduate-level seminar on scan statistics.
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Joseph Naus: Father of the Scan Statistic -- Precedence-Type Tests for the Comparison of Treatments with a Control -- Extreme Value Results for Scan Statistics -- Boundary Crossing Probability Computationsin the Analysis of Scan Statistics -- Approximations for Two-Dimensional Variable Window Scan Statistics -- Applications of Spatial Scan Statistics: A Review -- Extensions of the Scan Statistic for the Detection and Inference of SpatialClusters -- 1-Dependent Stationary Sequences and Applications to Scan Statistics -- Scan Statistics in Genome-Wide Scan for Complex Trait Loci -- On Probabilities for Complex Switching Rules in Sampling Inspection -- Bayesian Network Scan Statistics for Multivariate Pattern Detection -- ULS Scan Statistic for Hotspot Detection with Continuous Gamma Response -- False Discovery Control for Scan Clustering -- Martingale Methods for Patterns and Scan Statistics -- How Can Pattern Statistics Be Useful for DNA Motif Discovery? -- Occurrence of Patterns and Motifs in Random Strings -- Detection of Disease Clustering.

Scan statistics is currently one of the most active and important areas of research in applied probability and statistics, having applications to a wide variety of fields: archaeology, astronomy, bioinformatics, biosurveillance, molecular biology, genetics, computer science, electrical engineering, geography, material sciences, physics, reconnaissance, reliability and quality control, telecommunication, and epidemiology. Filling a gap in the literature, this self-contained volume brings together a collection of selected chapters illustrating the depth and diversity of theory, methods and applications in the area of scan statistics. Key features: * Chapters are written by leading experts in the field. * Features many current results and highlights new directions for future research. * Includes challenging theoretical methodological research problems. * Presentation is accessible to statisticians as well as to scientists from other disciplines where scan statistics are employed. * Real-world applications to areas such as bioinformatics and biosurveillance are emphasized. * Contains extensive references to research articles, books, and relevant computer software. Scan Statistics is an excellent reference for graduate students and researchers in applied probability and statistics, as well as for scientists in biology, computer science, pharmaceutical science, medicine, geography, quality control, communications, and epidemiology. The work may also be used as a textbook for a graduate-level seminar on scan statistics.

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