On distance in total variation between image measures
Autor: | Youri Davydov |
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Rok vydání: | 2017 |
Předmět: |
Statistics and Probability
Degree (graph theory) Gaussian Image (category theory) Probability (math.PR) 010102 general mathematics Gaussian binomial coefficient 01 natural sciences Combinatorics 010104 statistics & probability symbols.namesake Total variation Asymptotically optimal algorithm 60E05 (Primary) 60E15 60A10 (Secondary) Simple (abstract algebra) FOS: Mathematics symbols 0101 mathematics Statistics Probability and Uncertainty Random variable Mathematics - Probability Mathematics |
Zdroj: | Statistics & Probability Letters. 129:393-400 |
ISSN: | 0167-7152 |
DOI: | 10.1016/j.spl.2017.06.022 |
Popis: | We are interested in the estimation of the distance in total variation $$ \Delta := \|P_{f(X)} - P_{g(X)}\|_{\mathrm var} $$ between distributions of random variables $f(X)$ and $g(X)$ in terms of proximity of $f$ and $g.$ We propose a simple general method of estimating $\Delta$. For Gaussian and trigonometrical polynomials it gives an asymptotically optimal result (when the degree tends to $\infty$). Comment: 13 pages |
Databáze: | OpenAIRE |
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