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  2. Delta method - Wikipedia

    en.wikipedia.org/wiki/Delta_method

    By definition, a consistent estimator B converges in probability to its true value β, and often a central limit theorem can be applied to obtain asymptotic normality: (,),

  3. Convergence of random variables - Wikipedia

    en.wikipedia.org/wiki/Convergence_of_random...

    then S n converges almost surely if and only if S n converges in probability. The proof can be found in Page 126 (Theorem 5.3.4) of the book by Kai Lai Chung. [13] However, for a sequence of mutually independent random variables, convergence in probability does not imply almost sure convergence. [14] [circular reference]

  4. Limit of a function - Wikipedia

    en.wikipedia.org/wiki/Limit_of_a_function

    Although implicit in the development of calculus of the 17th and 18th centuries, the modern idea of the limit of a function goes back to Bolzano who, in 1817, introduced the basics of the epsilon-delta technique (see (ε, δ)-definition of limit below) to define continuous functions. However, his work was not known during his lifetime.

  5. Nonstandard analysis - Wikipedia

    en.wikipedia.org/wiki/Nonstandard_analysis

    H. Jerome Keisler, David Tall, and other educators maintain that the use of infinitesimals is more intuitive and more easily grasped by students than the "epsilon–delta" approach to analytic concepts. [10] This approach can sometimes provide easier proofs of results than the corresponding epsilon–delta formulation of the proof.

  6. Limit (mathematics) - Wikipedia

    en.wikipedia.org/wiki/Limit_(mathematics)

    Augustin-Louis Cauchy in 1821, [6] followed by Karl Weierstrass, formalized the definition of the limit of a function which became known as the (ε, δ)-definition of limit. The modern notation of placing the arrow below the limit symbol is due to G. H. Hardy, who introduced it in his book A Course of Pure Mathematics in 1908. [7]

  7. Central limit theorem - Wikipedia

    en.wikipedia.org/wiki/Central_limit_theorem

    The occurrence of the Gaussian probability density 1 = e −x 2 in repeated experiments, in errors of measurements, which result in the combination of very many and very small elementary errors, in diffusion processes etc., can be explained, as is well-known, by the very same limit theorem, which plays a central role in the calculus of probability.

  8. Limit inferior and limit superior - Wikipedia

    en.wikipedia.org/wiki/Limit_inferior_and_limit...

    In mathematical analysis, limit superior and limit inferior are important tools for studying sequences of real numbers.Since the supremum and infimum of an unbounded set of real numbers may not exist (the reals are not a complete lattice), it is convenient to consider sequences in the affinely extended real number system: we add the positive and negative infinities to the real line to give the ...

  9. Continuous function - Wikipedia

    en.wikipedia.org/wiki/Continuous_function

    The epsilon–delta definition of a limit was introduced to formalize the definition of continuity. Continuity is one of the core concepts of calculus and mathematical analysis, where arguments and values of functions are real and complex numbers. The concept has been generalized to functions between metric spaces and between topological spaces.