An empirical study of moment estimators for quantile approximation

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Title

An empirical study of moment estimators for quantile approximation

Content partner

University of Waikato

Collection

ResearchCommons@Waikato

Description

We empirically evaluate lightweight moment estimators for the single-pass quantile approximation problem, including maximum entropy methods and orthogonal series with Fourier, Cosine, Legendre, Chebyshev and Hermite basis functions. We show how to apply stable summation formulas to offset numerical precision issues for higher-order moments, leading to reliable single-pass moment estimators up to order 15. Additionally, we provide an algorithm for GPU-accelerated quantile approximation based o...

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Format

Research paper

Research format

Journal article

Date created

2021

URL

https://hdl.handle.net/10289/14197

Related subjects

computer science / distributon functions / statistical software / data mining / machine learning algorithms / density estimation / quantiles / data streams

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