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Modern Time Series Forecasting with Python

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Introduction to Probability, Second Edition

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Series series Chapman & Hall/CRC Texts in Statistical Science
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Examples In Markov Decision Processes

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Series Book 2 - Imperial College Press Optimization Series
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This invaluable book provides approximately eighty examples illustrating the theory of controlled discrete-time Markov processes. Except for applications of the theory to real-life problems like stock exchange, queues, gambling, optimal search etc, the main attention is paid to counter-intuitive, unexpected properties of optimization problems. Such examples illustrate the importance of conditions
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Fundamentals of Computational Neuroscience

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Computational neuroscience is the theoretical study of the brain to uncover the principles and mechanisms that guide the development, organization, information processing, and mental functions of the nervous system. Although not a new area, it is only recently that enough knowledge has been gathered to establish computational neuroscience as a scientific discipline in its own right. Given the ... Read more

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Computational neuroscience is the theoretical study of the brain to uncover the principles and mechanisms that guide the development, organization, information processing, and mental functions of the nervous system. Although not a new area, it is only recently that enough knowledge has been gathered to establish computational neuroscience as a scientific discipline in its own right. Given the
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Pandemics: Insurance and Social Protection

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Series series Springer Actuarial
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This open access book collects expert contributions on actuarial modelling and related topics, from machine learning to legal aspects, and reflects on possible insurance designs during an epidemic/pandemic.Starting by considering the impulse given by COVID-19 to the insurance industry and to actuarial research, the text covers compartment models, mortality changes during a pandemic, risk-sharing
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Principles of Nonlinear Filtering Theory

by Stephen S.-T. Yau, Xiuqiong Chen, Xiaopei Jiao, Jiayi Kang, Zeju Sun, Yangtianze Tao ...

Series series Mathematics and Statistics (R0)
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This text presents a comprehensive and unified treatment of nonlinear filtering theory, with a strong emphasis on its mathematical underpinnings. It is tailored to meet the needs of a diverse readership, including mathematically inclined engineers and scientists at both graduate and post-graduate levels. What sets this book apart from other treatments of the topic is twofold. Firstly, it offers a
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Festschrift Masatoshi Fukushima: In Honor Of Masatoshi Fukushima's Sanju

by Zhen-qing Chen, Niels Jacob, Masayoshi Takeda, Toshihiro Uemura ...

Series Book 17 - Interdisciplinary Mathematical Sciences
This book contains original research papers by leading experts in the fields of probability theory, stochastic analysis, potential theory and mathematical physics. There is also a historical account on Masatoshi Fukushima's contribution to mathematics, as well as authoritative surveys on the state of the art in the field. ... Read more

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This book contains original research papers by leading experts in the fields of probability theory, stochastic analysis, potential theory and mathematical physics. There is also a historical account on Masatoshi Fukushima's contribution to mathematics, as well as authoritative surveys on the state of the art in the field.
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Teaching and Learning Stochastics

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This book presents a collection of selected papers that represent the current variety of research on the teaching and learning of probability. The respective chapters address a diverse range of theoretical, empirical and practical aspects underpinning the teaching and learning of probability, curricular issues, probabilistic reasoning, misconceptions and biases, as well as their pedagogical
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Series series Mathematics and Statistics (R0)
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This book demonstrates how nonlinear/non-Gaussian Bayesian time series estimation methods were used to produce a probability distribution of potential MH370 flight paths. It provides details of how the probabilistic models of aircraft flight dynamics, satellite communication system measurements, environmental effects and radar data were constructed and calibrated. The probability distribution was
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Fundamentals of Stochastic Models

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Stochastic modeling is a set of quantitative techniques for analyzing practical systems with random factors. This area is highly technical and mainly developed by mathematicians. Most existing books are for those with extensive mathematical training; this book minimizes that need and makes the topics easily understandable.Fundamentals of Stochastic Models offers many practical examples and ... Read more

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Asymptotics for Fractional Processes develops an approach to the large-sample analysis of fractional partial-sum processes, featuring long memory increments. Long memory in a time series, equivalently called strong dependence, is usually defined to mean that the autocovariance sequence is non-summable. The processes studied have a linear moving average representation with a single parameter,
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Particle emission concept and probabilistic consideration of the development of infections in systems

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The book describes the possibility of making a probabilistic prognosis, which uses the mean n-day logarithm of case numbers in the past to determine an exponent for a probability density for a prognosis, as well as the particle emission concept, which is derived from contact and distribution rates that increase the exponent of the probable development to the extent that a group of people can be
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This book focuses on quantitative approximation results for weak limit theorems when the target limiting law is infinitely divisible with finite first moment. Two methods are presented and developed to obtain such quantitative results. At the root of these methods stands a Stein characterizing identity discussed in the third chapter and obtained thanks to a covariance representation of infinitely ... Read more

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This book focuses on quantitative approximation results for weak limit theorems when the target limiting law is infinitely divisible with finite first moment. Two methods are presented and developed to obtain such quantitative results. At the root of these methods stands a Stein characterizing identity discussed in the third chapter and obtained thanks to a covariance representation of infinitely
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PRE-ORDER

Master ML for financial systems with practical workflows using Python, GenAI, and modern ML deployment tools. Includes hands-on projects in trading, fraud detection, portfolio optimization, and regulatory compliance.Key FeaturesPractical machine learning techniques for financial data and time-series forecastingApply GenAI for synthetic data generation, financial NLP, and reporting automationDeploy
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General Stochastic Measures

Integration, Path Properties and Equations

by Vadym M. Radchenko ...

This book is devoted to the study of stochastic measures (SMs). An SM is a sigma-additive in probability random function, defined on a sigma-algebra of sets. SMs can be generated by the increments of random processes from many important classes such as square-integrable martingales and fractional Brownian motion, as well as alpha-stable processes. SMs include many well-known stochastic integrators ... Read more

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This book is devoted to the study of stochastic measures (SMs). An SM is a sigma-additive in probability random function, defined on a sigma-algebra of sets. SMs can be generated by the increments of random processes from many important classes such as square-integrable martingales and fractional Brownian motion, as well as alpha-stable processes. SMs include many well-known stochastic integrators
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Semi-Markov Models

Control of Restorable Systems with Latent Failures

by Yuriy E Obzherin, Elena G Boyko ...

Featuring previously unpublished results, Semi-Markov Models: Control of Restorable Systems with Latent Failures describes valuable methodology which can be used by readers to build mathematical models of a wide class of systems for various applications. In particular, this information can be applied to build models of reliability, queuing systems, and technical control. Beginning with a brief ... Read more

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Featuring previously unpublished results, Semi-Markov Models: Control of Restorable Systems with Latent Failures describes valuable methodology which can be used by readers to build mathematical models of a wide class of systems for various applications. In particular, this information can be applied to build models of reliability, queuing systems, and technical control. Beginning with a brief
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Recommended For You

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Festschrift Masatoshi Fukushima: In Honor Of Masatoshi Fukushima's Sanju

Teaching and Learning Stochastics

Stochastic Processes and Financial Mathematics

Classical and Spatial Stochastic Processes

Modeling Practical Problems in Complex Systems

Mathematics Of Open Quantum Systems, The: Dissipative And Non-unitary Representations And Quantum Measurements

Applied Probability and Stochastic Processes

Earthquake Hazard and Risk

Simulation

Bayesian Methods in the Search for MH370

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