JOURNAL ARTICLE

Non-linear Functionals Preserving Normal Distribution and Their Asymptotic Normality

Abstract

We introduce sufficiently wide classes of non--linear functionals preserving normal (Gaussian) distribution and establish various conditions under which a sequence of such functionals is asymptotically normal. As one of a consequence we obtain a generalization and sharpening of known results on the central limit theorem for weighted sums (linear functionals) of independent random variables.

Keywords:
Mathematics Central limit theorem Generalization Sharpening Asymptotic distribution Gaussian Limit (mathematics) Sequence (biology) Normality Normal distribution Applied mathematics Distribution (mathematics) Random variable Mathematical analysis Pure mathematics Estimator Statistics Computer science

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Citation History

Topics

Probability and Risk Models
Social Sciences →  Decision Sciences →  Management Science and Operations Research
advanced mathematical theories
Physical Sciences →  Mathematics →  Mathematical Physics
Stochastic processes and financial applications
Social Sciences →  Economics, Econometrics and Finance →  Finance

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