An Introduction to the Theory of Large Deviations

Target entity: An Introduction to the Theory of Large Deviations
Context triple: [Daniel Stroock, notableWork, An Introduction to the Theory of Large Deviations]

• A. Cramér’s theorem in large deviations
  Cramér’s theorem in large deviations is a fundamental result in probability theory that characterizes the exponential decay rate of tail probabilities for sums of independent, identically distributed random variables via a convex rate function.
• B. Freidlin–Wentzell theory
  Freidlin–Wentzell theory is a mathematical framework in probability that analyzes the behavior of stochastic dynamical systems under small random perturbations using large deviation principles.
• C. Modern Probability Theory and Its Applications
  "Modern Probability Theory and Its Applications" is a foundational textbook by Emanuel Parzen that systematically develops modern probability theory and demonstrates its use in a wide range of statistical and applied contexts.
• D. Introduction to Stochastic Control Theory
  Introduction to Stochastic Control Theory is a foundational textbook that systematically develops the theory and methods for controlling dynamical systems under uncertainty using probabilistic and stochastic-process tools.
• E. Kolmogorov's law of the iterated logarithm
  Kolmogorov's law of the iterated logarithm is a fundamental result in probability theory that precisely characterizes the almost-sure fluctuations of partial sums of independent random variables between the law of large numbers and the central limit theorem.
• F. None of above. chosen
• G. Unsure - the case is ambiguous/there is not enough information to decide.

Target entity: An Introduction to the Theory of Large Deviations
Target entity description: "An Introduction to the Theory of Large Deviations" is a mathematical monograph that systematically develops the probabilistic theory of large deviations, focusing on rigorous asymptotic analysis of rare events.

• A. Cramér’s theorem in large deviations
  Cramér’s theorem in large deviations is a fundamental result in probability theory that characterizes the exponential decay rate of tail probabilities for sums of independent, identically distributed random variables via a convex rate function.
• B. Freidlin–Wentzell theory
  Freidlin–Wentzell theory is a mathematical framework in probability that analyzes the behavior of stochastic dynamical systems under small random perturbations using large deviation principles.
• C. Modern Probability Theory and Its Applications
  "Modern Probability Theory and Its Applications" is a foundational textbook by Emanuel Parzen that systematically develops modern probability theory and demonstrates its use in a wide range of statistical and applied contexts.
• D. Introduction to Stochastic Control Theory
  Introduction to Stochastic Control Theory is a foundational textbook that systematically develops the theory and methods for controlling dynamical systems under uncertainty using probabilistic and stochastic-process tools.
• E. Kolmogorov's law of the iterated logarithm
  Kolmogorov's law of the iterated logarithm is a fundamental result in probability theory that precisely characterizes the almost-sure fluctuations of partial sums of independent random variables between the law of large numbers and the central limit theorem.
• F. None of above. chosen