Central Limit Theorems
The central limit theorem (abbreviated CLT) is one of the most startling results in probability theory. Loosely speaking, it expresses the fact that the sums of local and small independent disturbances (with finite variances) behave asymptotically, at least as Gaussian variables. The first CLT was stated and proved for symmetric and Bernoulli independent disturbances by A. De Moivre in the 18th century (Miscellanea anaJytica supplementum, 1730). This result was extended by P.S. Laplace in 1812 to general Bernoulli trials in his celebrated treatise Théorie analytique des probabilités.
KeywordsCentral Limit Theorem Empirical Process Triangular Array Centered Gaussian Process Interact Particle Model
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