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Books in Probability theory and stochastic processes

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    • Multidimensional Signal Processing

      • 1st Edition
      • Volume 54
      • February 1, 2026
      • English
      • Hardback
        9 7 8 0 4 4 3 4 1 4 6 5 7
      • eBook
        9 7 8 0 4 4 3 4 1 4 6 6 4
      Multidimensional Signal Processing volume of the “Handbook of Statistics” series isdedicated to presenting the latest developments and methodologies in multidimensional signalprocessing. The book aims to provide a comprehensive overview of the theories, models, andmethods that form the foundation of this field. Our goal is to cater to a broad audience of signal-processing practitioners. The chapters within this volume are meticulously curated to offerdetailed, educational content rather than conventional journal-style articles. Contributors to thisvolume are leading experts in the field, ensuring high-profile content that combines theoreticalrigor with practical insights. Through this comprehensive compilation, we aim to advance theknowledge and application of multidimensional signal processing, contributing significantly tothe broader fields of statistics and data science.

    • An Introduction to Stochastic Modeling

      • 5th Edition
      • September 17, 2025
      • Gabriel Lord + 1 more
      • English
      • Paperback
        9 7 8 0 4 4 3 3 1 5 5 2 7
      • eBook
        9 7 8 0 4 4 3 3 1 5 5 3 4
      An Introduction to Stochastic Modeling, Fifth Edition bridges the gap between basic probability and an intermediate level course in stochastic processes, serving as the foundation for either a one-semester or two-semester course in stochastic processes for students familiar with elementary probability theory and calculus. The objectives are to introduce students to the standard concepts and methods of stochastic modeling, to illustrate the rich diversity of applications of stochastic processes in the applied sciences, and to provide an integrated treatment of theory, applications and practical implementation. A well-regarded resource for many years, the text is an ideal foundation for a broad range of students.

    • Statistics in Industry and Government

      • 1st Edition
      • Volume 53
      • August 6, 2025
      • English
      • Hardback
        9 7 8 0 4 4 3 3 1 4 2 2 3
      • eBook
        9 7 8 0 4 4 3 3 1 4 2 3 0
      Statistics in Industry and Government covers industrial quality control and high-class quality maintenance in products. The book aims to cover as many applications that use statistics as an underlying tool in bringing the best quality products and industrial designs. Chapters in this new release include Analysis of Official Time Series with Ecce Signum, an R Package for Multivariate Signal Extraction and Forecasting, The Maturity Structure of Public Debt: A Granular Approach Using Indian Data, Harnessing the power of spherical intersection: A less arbitrary unsupervised learning method applied to pattern recognition within financial data, and much more.Other chapters in this release include The Use of Causal Inference with Structural Models in Industry, MSME Statistics in India, The Importance of Accurate, Timely, Credible Crime Data to Inform Crime and Justice Policy, Combining Information from Multiple Sources in Official Statistics, Active Learning of Computer Experiment with both Quantitative and Qualitative Inputs, On the use of machine learning methods for missing data problems, Optimal Experimental Planning for Experiments Based on Coherent Systems with Industrial Applications, and more.

    • Stochastic Theory of Service Systems

      • 1st Edition
      • May 23, 2025
      • L. Kosten
      • I. N. Sneddon + 1 more
      • English
      • Paperback
        9 7 8 1 4 8 3 1 1 8 1 6 1
      • eBook
        9 7 8 1 4 8 3 1 5 0 5 8 1
      International Series of Monographs in Pure and Applied Mathematics, Volume 103: Stochastic Theory of Service Systems focuses on the principles, methodologies, and approaches involved in the stochastic theory of service systems. The publication first examines the general description of service systems, characteristics of the arrival process, standard cases, and the distribution of waiting-times in the system M/M/c-delay. Discussions focus on "random" condition, probability of delay and average waiting-time for the system M/M/c-delay, Engset formula, and probability of blocking for the system M/M/c-blocking. The text then examines general holding-time assumption, non-stationary behavior, and priority. Topics include pre-emptive priority, transient behavior of the system M/G/1-delay, Markov process with a finite number of states, and hyperexponential distributions. The manuscript takes a look at simulation, arrival and service in batches, and restricted availability, including approximate determination of probabilities of blocking, "unscheduled ferry problem", principles of roulette simulation, and implementation of randomness. The publication is a dependable source material for researchers interested in the stochastic theory of service systems.

    • Markov Chains: Theory and Applications

      • 1st Edition
      • Volume 52
      • April 15, 2025
      • English
      • Hardback
        9 7 8 0 4 4 3 2 9 5 7 6 8
      • eBook
        9 7 8 0 4 4 3 2 9 5 7 7 5
      Markov Chains: Theory and Applications, Volume 52 in the Handbook of Statistics series, highlights new advances in the field, with this new volume presenting interesting chapters on topics such as Markov Chain Estimation, Approximation, and Aggregation for Average Reward Markov Decision Processes and Reinforcement Learning, Ladder processes: symmetric functions and semigroups, Continuous-time Markov Chains and Models: Study via Forward Kolmogorov System, Analysis of Data Following Finite-State Continuous-Time Markov Chains, Computational applications of poverty measurement through Markov model for income classes, and more.Other sections cover Estimation and calibration of continuous time Markov chains, Additive High-Order Markov Chains, The role of the random-product technique in the theory of Markov chains on a countable state space., On estimation problems based on type I Longla copulas, and Long time behavior of continuous time Markov chains.

    • Probability Models

      • 1st Edition
      • Volume 51
      • September 27, 2024
      • English
      • Hardback
        9 7 8 0 4 4 3 2 9 3 2 8 3
      • eBook
        9 7 8 0 4 4 3 2 9 3 2 9 0
      Probability Models, Volume 51 in the Handbook of Statistics series, highlights new advances in the field, with this new volume presenting interesting chapters on Stein’s methods, Probabilities and thermodynamics third law, Random Matrix Theory, General tools for understanding fluctuations of random variables, An approximation scheme to compute the Fisher-Rao distance between multivariate normal distributions, Probability Models Applied to Reliability and Availability Engineering, Backward stochastic differential equation– Stochastic optimization theory and viscous solution of HJB equation, and much more.Additional chapters cover Probability Models in Machine Learning, The recursive stochastic algorithm, randomized urn models and response-adaptive randomization in clinical trials, Random matrix theory: local laws and applications, KOO methods and their high-dimensional consistencies in some multivariate models, Fourteen Lectures on Inference for Stochastic Processes, and A multivariate cumulative damage model and some applications.

    • Modeling and Analysis of Longitudinal Data

      • 1st Edition
      • Volume 50
      • February 7, 2024
      • English
      • Hardback
        9 7 8 0 4 4 3 1 3 6 5 1 1
      • eBook
        9 7 8 0 4 4 3 1 3 6 5 2 8
      Longitudinal Data Analysis, Volume 50 in the Handbook of Statistics series covers how data consists of a series of repeated observations of the same subjects over an extended time frame and is thus useful for measuring change. Such studies and the data arise in a variety of fields, such as health sciences, genomic studies, experimental physics, sociology, sports and student enrollment in universities. For example, in health studies, intra-subject correlation of responses must be accounted for, covariates vary with time, and bias can arise if patients drop out of the study.

    • Artificial Intelligence

      • 1st Edition
      • Volume 49
      • August 25, 2023
      • English
      • Hardback
        9 7 8 0 4 4 3 1 3 7 6 3 1
      • eBook
        9 7 8 0 4 4 3 1 3 7 6 4 8
      Artificial Intelligence, Volume 49 in the Handbook of Statistics series, highlights new advances in the field, with this new volume presenting interesting chapters on a variety of timely topics. Chapters in this new release include AI Teacher-Student based Adaptive Structural Deep Learning Model and Its Estimating Uncertainty of Image Data, Machine-derived Intelligence: Computations Beyond the Null Hypothesis, Object oriented basis of artificial intelligence methodologies I in Judicial Systems in India, Artificial Intelligence in Systems Biology, Machine-Learning in Geometry and Physics, Innovation and Machine Learning: Crowdsourcing Open-Source Natural Language Processing (NLP) Algorithms to Advance Public Health Surveillance, and more. Other chapters cover Learning and identity testing of Markov chains, Data privacy for machine learning and statistics, and The interface between AI and Mathematics.

    • Introduction to Probability Models

      • 13th Edition
      • June 30, 2023
      • Sheldon M. Ross
      • English
      • Paperback
        9 7 8 0 4 4 3 1 8 7 6 1 2
      • eBook
        9 7 8 0 4 4 3 1 8 7 6 0 5
      *Textbook and Academic Authors Association (TAA) McGuffey Longevity Award Winner, 2024*A trusted market leader for four decades, Sheldon Ross’s Introduction to Probability Models offers a comprehensive foundation of this key subject with applications across engineering, computer science, management science, the physical and social sciences and operations research. Through its hallmark exercises and real examples, this valuable course textIntroduction to Probability Models provides the reader with a comprehensive course in the subject, from foundations to advanced topics.

    • Deep Learning

      • 1st Edition
      • Volume 48
      • February 28, 2023
      • English
      • Hardback
        9 7 8 0 4 4 3 1 8 4 3 0 7
      • eBook
        9 7 8 0 4 4 3 1 8 4 3 1 4
      Deep Learning, Volume 48 in the Handbook of Statistics series, highlights new advances in the field, with this new volume presenting interesting chapters on a variety of timely topics, including Generative Adversarial Networks for Biometric Synthesis, Data Science and Pattern Recognition, Facial Data Analysis, Deep Learning in Electronics, Pattern Recognition, Computer Vision and Image Processing, Mechanical Systems, Crop Technology and Weather, Manipulating Faces for Identity Theft via Morphing and Deepfake, Biomedical Engineering, and more.