Sequential Change Detection and Hypothesis Testing by Alexander Tartakovsky
Statistical methods for sequential hypothesis testing and changepoint detection have applications across many fields, including quality control, biomedical engineering, communication networks, econometrics, image processing, security, etc. This book presents an overview of methodology in these related areas, providing a synthesis of research from the last few decades. The methods are illustrated through real data examples, and software is referenced where possible. The emphasis is on providing all the theoretical details in a unified framework, with pointers to new research directions.-
Statistical Inference
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Practical Risk Theory for Actuaries
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Analysis of Survival Data
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Generalized Linear Models with Random Effects
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An Introduction to the Bootstrap
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Queues
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Transformation and Weighting in Regression
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Sequential Analysis
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Asymptotic Analysis of Mixed Effects Models
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Statistics for Long-Memory Processes
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Analysis of Infectious Disease Data
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ROC Curves for Continuous Data
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Missing Data in Longitudinal Studies
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Analyzing and Modeling Rank Data
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Stochastic Geometry
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Semimartingales and their Statistical Inference
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Accelerated Life Models
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Statistical Analysis of Spatial and Spatio-Temporal Point Patterns
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Quasi-Least Squares Regression
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Large Covariance and Autocovariance Matrices
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Design and Analysis of Cross-Over Trials
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Analysis of Variance for Functional Data
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Pareto Distributions
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Analysis of Incomplete Multivariate Data
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Simultaneous Inference in Regression
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Gaussian Markov Random Fields
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Sufficient Dimension Reduction
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Markov Models & Optimization
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Multidimensional Scaling
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Biplots
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Analog Est Methods Econometric
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Measurement Error in Nonlinear Models
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Predictive Inference
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Subjective Probability Models for Lifetimes
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Smoothing Splines
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Bayesian Inference for Partially Identified Models
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Maximum Likelihood Estimation for Sample Surveys
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Mean Field Simulation for Monte Carlo Integration
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Robust Nonparametric Statistical Methods
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The Statistical Analysis of Multivariate Failure Time Data
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Measuring Statistical Evidence Using Relative Belief
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Statistical Methods for Stochastic Differential Equations
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| ISBN 13 | |
| ISBN 10 | |
| Title | Sequential Change Detection and Hypothesis Testing |
| Author | Alexander Tartakovsky |
| Series | |
| Condition | Unavailable |
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| Cover note | Book picture is for illustrative purposes only, actual binding, cover or edition may vary. |
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