Theory of Stochastic Objects: Probability, Stochastic Processes, and Inference
Athanasios Christou Micheas explores stochastic objects, covering probability, stochastic processes, and inference techniques.
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Athanasios Christou Micheas explores stochastic objects, covering probability, stochastic processes, and inference techniques.
Rodríguez and Mendes’ Probability, Decisions, and Games introduces probability, decision-making, and game theory with practical R examples, ideal for beginners.
Hoffmann-Jorgensen’s Probability with a View Toward Statistics explores probability theory with a focus on its applications in statistical analysis.
Linde’s Probability Theory provides a foundational introduction to probability and statistics, ideal for beginners with practical examples.
Shorack’s Probability for Statisticians delves into probability theory with a focus on statistical applications and theoretical foundations.
Rachev, Höchstötter, Fabozzi, and Focardi’s book applies probability and statistics to finance with real-world examples and case studies.
Forsyth’s Probability and Statistics for Computer Science covers key methods for computer science, including practical examples and problem-solving techniques.
Blitzstein and Hwang’s second edition introduces probability with engaging content and practical problem-solving techniques, ideal for learners & practitioners.
T.T. Soong’s guide to probability and statistics provides engineers with essential techniques and practical examples for solving real-world problems.
Biagini and Campanino provide a clear introduction to probability and statistics with de Finetti’s approach, making complex concepts accessible.