Nonlinear prediction via Hermite transformation

General prediction formulas involving Hermite polynomials are developed for time series expressed as a transformation of a Gaussian process. The prediction gains over linear predictors are examined numerically, demonstrating the improvement of nonlinear prediction.

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Bibliographic Details
Published inStatistical theory and related fields Vol. 5; no. 1; pp. 49 - 54
Main Authors McElroy, Tucker, Das, Srinjoy
Format Journal Article
LanguageEnglish
Published Taylor & Francis 02.01.2021
Taylor & Francis Group
Subjects
Gaussian transformation
Hermite polynomial
nonlinear forecasting
time series
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Summary:General prediction formulas involving Hermite polynomials are developed for time series expressed as a transformation of a Gaussian process. The prediction gains over linear predictors are examined numerically, demonstrating the improvement of nonlinear prediction.
ISSN:2475-4269
2475-4277
DOI:10.1080/24754269.2020.1856589