Stochastic Processes Applied Probability by Hossain (8 results)

PAP. Condition: New. New Book. Shipped from UK. Established seller since 2000.

PAP. Condition: New. New Book. Shipped from UK. Established seller since 2000.

Taschenbuch. Condition: Neu. Neuware - Master stochastic processes beyond the basics-with clarity, rigor, and real understanding.Stochastic Processes & Applied Probability: Volume 2 is a carefully structured second course designed for college and university students, engineers, quantitative analysts, and self-learners ready to move beyond introductory probability and Markov chains into the deeper mathematics of stochastic modeling.Building directly on foundational probability and stochastic-process concepts, this volume develops the theory and applications of renewal processes, martingales, Brownian motion, stochastic calculus, stochastic differential equations, diffusion models, filtering, and simulation in a clear and accessible style.Unlike many advanced probability texts that assume heavy mathematical maturity and skip intermediate reasoning, this book emphasizes step-by-step learning, intuition, and mastery through worked examples while maintaining mathematical rigor.Inside this volume, you will learn: - Renewal theory and long-run stochastic behavior- Renewal functions and the elementary renewal theorem- Age, residual life, and the inspection paradox- Martingales and conditional expectation as working tools- Filtrations, stopping times, and optional stopping- Martingale convergence and inequalities- Brownian motion and sample-path behavior- The Itô integral and stochastic integration- Itô's formula and stochastic calculus- Stochastic differential equations (SDEs)- Diffusions and the Fokker-Planck equation- Hidden Markov models and filtering methods- Stochastic simulation and computational probabilityThis book features: Clear explanations with minimal unnecessary abstractionFully worked examples throughoutDiagnostic reviews and prerequisite checksCommon-trap and mistake-prevention sectionsPractice, Apply, and Challenge problem setsStep-by-step solutionsFormula summaries and reference materialSelf-study and classroom-friendly organizationWhether you are studying probability, applied mathematics, statistics, quantitative finance, machine learning, operations research, engineering, or stochastic modeling, this book provides a rigorous yet approachable pathway into modern stochastic processes and applied probability.Volume 2 continues the journey from foundational stochastic models to the powerful tools used in contemporary science, engineering, finance, and data-driven systems.

Taschenbuch. Condition: Neu. Neuware.

Condition: New. Print on Demand.

Condition: New. Print on Demand.

Paperback. Condition: new. Paperback. Master stochastic processes with clarity, rigor, and real-world insight.Stochastic Processes & Applied Probability: A First Course in Modeling Random Systems - Volume 1 is a carefully structured introduction designed for upper-level undergraduate and early graduate students in mathematics, statistics, engineering, operations research, economics, and data science.Unlike many traditional texts that are overly abstract or theorem-heavy, this book emphasizes understanding through worked examples, modeling intuition, and step-by-step problem solving.This volume develops the mathematical foundation behind systems that evolve under uncertainty - from random walks and queueing systems to Markov chains and Brownian motion.Inside this book you will learn: - Probability refresher and conditioning- Law of total probability and Bayes' theorem- Conditional expectation and modeling intuition- Random walks and gambler's ruin- Generating functions and branching processes- Discrete-time Markov chains- State classification and long-run behavior- Absorbing chains and first-passage analysis- The Poisson process- Continuous-time Markov chains- Queueing theory and M/M systems- Brownian motion and introductory diffusion modelsThis textbook includes: Fully worked examples with clear step-by-step solutions Progressive difficulty from fundamentals to applications Diagnostic reviews and mastery checkpoints Common-trap sections to prevent frequent mistakes Retention reviews and cumulative practice Complete problem solutions and answer summaries Modeling-focused explanations that connect theory with applicationsWhether you are studying stochastic processes for mathematics, engineering, data science, operations research, finance, or self-study, this book provides a practical and rigorous path into one of the most powerful areas of applied mathematics.Learn the theory. Understand the models. Apply stochastic thinking with confidence. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.

Paperback. Condition: new. Paperback. Master stochastic processes beyond the basics-with clarity, rigor, and real understanding.Stochastic Processes & Applied Probability: Volume 2 is a carefully structured second course designed for college and university students, engineers, quantitative analysts, and self-learners ready to move beyond introductory probability and Markov chains into the deeper mathematics of stochastic modeling.Building directly on foundational probability and stochastic-process concepts, this volume develops the theory and applications of renewal processes, martingales, Brownian motion, stochastic calculus, stochastic differential equations, diffusion models, filtering, and simulation in a clear and accessible style.Unlike many advanced probability texts that assume heavy mathematical maturity and skip intermediate reasoning, this book emphasizes step-by-step learning, intuition, and mastery through worked examples while maintaining mathematical rigor.Inside this volume, you will learn: - Renewal theory and long-run stochastic behavior- Renewal functions and the elementary renewal theorem- Age, residual life, and the inspection paradox- Martingales and conditional expectation as working tools- Filtrations, stopping times, and optional stopping- Martingale convergence and inequalities- Brownian motion and sample-path behavior- The Ito integral and stochastic integration- Ito's formula and stochastic calculus- Stochastic differential equations (SDEs)- Diffusions and the Fokker-Planck equation- Hidden Markov models and filtering methods- Stochastic simulation and computational probabilityThis book features: Clear explanations with minimal unnecessary abstractionFully worked examples throughoutDiagnostic reviews and prerequisite checksCommon-trap and mistake-prevention sectionsPractice, Apply, and Challenge problem setsStep-by-step solutionsFormula summaries and reference materialSelf-study and classroom-friendly organizationWhether you are studying probability, applied mathematics, statistics, quantitative finance, machine learning, operations research, engineering, or stochastic modeling, this book provides a rigorous yet approachable pathway into modern stochastic processes and applied probability.Volume 2 continues the journey from foundational stochastic models to the powerful tools used in contemporary science, engineering, finance, and data-driven systems. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.