Markov processes for stochastic modeling / / Oliver C. Ibe, University of Massachusetts, Lowell, MA, USA

• Record Nr.: UNINA9910815457703321
• Autore: Ibe Oliver C
• Pubbl/distr/stampa: Amsterdam, Netherlands, : Elsevier, c2013; London : , : Elsevier, , 2013
• ISBN: 0-12-407839-7
• Edizione: [2nd ed.]
• Descrizione fisica: 1 online resource (xviii, 494 pages) : illustrations
• Collana: Elsevier insights Markov processes for stochastic modeling
• Disciplina: 519.233
• Soggetti: Markov processes; Stochastic processes
• Lingua di pubblicazione: Inglese
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Note generali: Previous edition: Amsterdam; London: Academic, 2009.
• Nota di bibliografia: Includes bibliographical references.
• Nota di contenuto: Front Cover; Markov Processes for Stochastic Modeling; Copyright page; Contents; Acknowledgments; Preface to the Second Edition; Preface to the First Edition; 1 Basic Concepts in Probability; 1.1 Introduction; 1.1.1 Conditional Probability; 1.1.2 Independence; 1.1.3 Total Probability and the Bayes' Theorem; 1.2 Random Variables; 1.2.1 Distribution Functions; 1.2.2 Discrete Random Variables; 1.2.3 Continuous Random Variables; 1.2.4 Expectations; 1.2.5 Expectation of Nonnegative Random Variables; 1.2.6 Moments of Random Variables and the Variance; 1.3 Transform Methods; 1.3.1 The s-Transform; 1.3.2 The z-Transform1.4 Bivariate Random Variables; 1.4.1 Discrete Bivariate Random Variables; 1.4.2 Continuous Bivariate Random Variables; 1.4.3 Covariance and Correlation Coefficient; 1.5 Many Random Variables; 1.6 Fubini's Theorem; 1.7 Sums of Independent Random Variables; 1.8 Some Probability Distributions; 1.8.1 The Bernoulli Distribution; 1.8.2 The Binomial Distribution; 1.8.3 The Geometric Distribution; 1.8.4 The Pascal Distribution; 1.8.5 The Poisson Distribution; 1.8.6 The Exponential Distribution; 1.8.7 The Erlang Distribution; 1.8.8 Normal Distribution; 1.9 Limit Theorems; 1.9.1 Markov Inequality1.9.2 Chebyshev Inequality; 1.9.3 Laws of Large Numbers; 1.9.4 The Central Limit Theorem; 1.10 Problems; 2 Basic Concepts in Stochastic Processes; 2.1 Introduction; 2.2 Classification of Stochastic Processes; 2.3 Characterizing a Stochastic Process; 2.4 Mean ; and Autocorrelation Function of a Stochastic Process; 2.5 Stationary Stochastic Processes; 2.5.1 Strict-Sense Stationary Processes; 2.5.2 Wide-Sense Stationary Processes; 2.6 Ergodic Stochastic Processes; 2.7 Some Models of Stochastic Processes; 2.7.1 Martingales; Stopping Times; 2.7.2 Counting Processes; 2.7.3 Independent Increment Processes2.7.4 Stationary Increment Process; 2.7.5 Poisson Processes; Interarrival Times for the Poisson Process; Compound Poisson Process; Combinations of Independent Poisson Processes; Competing Independent Poisson Processes; Subdivision of a Poisson Process; 2.8 Problems; 3 Introduction to Markov Processes; 3.1 Introduction; 3.2 Structure of Markov Processes; 3.3 Strong Markov Property; 3.4 Applications of Discrete-Time Markov Processes; 3.4.1 Branching Processes; 3.4.2 Social Mobility; 3.4.3 Markov Decision Processes; 3.5 Applications of Continuous-Time Markov Processes3.5.1 Queueing Systems; 3.5.2 Continuous-Time Markov Decision Processes; 3.5.3 Stochastic Storage Systems; 3.6 Applications of Continuous-State Markov Processes; 3.6.1 Application of Diffusion Processes to Financial Options; 3.6.2 Applications of Brownian Motion; 3.7 Summary; 4 Discrete-Time Markov Chains; 4.1 Introduction; 4.2 State-Transition Probability Matrix; 4.2.1 The n-Step State-Transition Probability; 4.3 State-Transition Diagrams; 4.4 Classification of States; 4.5 Limiting-State Probabilities; 4.5.1 Doubly Stochastic Matrix; 4.6 Sojourn Time
• Sommario/riassunto: Markov processes are processes that have limited memory. In particular, their dependence on the past is only through the previous state. They are used to model the behavior of many systems including communications systems, transportation networks, image segmentation and analysis, biological systems and DNA sequence analysis, random atomic motion and diffusion in physics, social mobility, population studies, epidemiology, animal and insect migration, queueing systems, resource management, dams, financial engineering, actuarial science, and decision systems. Covering a wide range of

American Horror Fiction and Class : From Poe to Twilight / / by David Simmons

• Record Nr.: UNINA9910255088903321
• Autore: Simmons David
• Pubbl/distr/stampa: London : , : Palgrave Macmillan UK : , : Imprint : Palgrave Macmillan, , 2017
• ISBN: 9781137532800; 1137532807
• Edizione: [1st ed. 2017.]
• Descrizione fisica: 1 online resource (IX, 201 p.)
• Collana: Palgrave Gothic, , 2634-6222
• Disciplina: 306.0973
• Soggetti: Ethnology - America; Culture; Culture - Study and teaching; Fiction; Popular culture; Film genres; American Culture; Cultural Theory; Fiction Literature; Popular Culture; Genre Studies
• Lingua di pubblicazione: Inglese
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Nota di bibliografia: Includes bibliographical references at the end of each chapters and index.
• Nota di contenuto: 1. Introduction: Establishing the Place of Class in US Gothic and Horror Fiction -- 2. Class and Horror Fiction during the Early Twentieth Century -- 3. Class and Horror Fiction at Mid-Century -- 4. Representing Class during the Horror Boom of the 1970s and 1980s -- 5. Horror Fiction and Class in the Contemporary1. Introduction: Establishing the Place of Class in US Gothic and Horror Fiction -- 2. Class and Horror Fiction during the Early Twentieth Century -- 3. Class and Horror Fiction at Mid-Century -- 4. Representing Class during the Horror Boom of the 1970s and 1980s -- 5. Horror Fiction and Class in the Contemporary Period. Period.
• Sommario/riassunto: In this book, Simmons argues that class, as much as race and gender, played a significant role in the development of Gothic and Horror fiction in a national context. From the classic texts of Edgar Allen Poe and Nathaniel Hawthorne right through to contemporary examples, such as the novels of Stephen King and Stephenie Meyer’s Twilight Series, class remains an ever present though understudied element. This study will appeal to scholars of American Studies, English literature, Media and Cultural Studies interested in class representations in the horror genre from the nineteenth century to the present day.