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Local Lead-Lag Relationships and Nonlinear Granger Causality: An Empirical Analysis

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Nonlinear Spectral Analysis: A Local Gaussian Approach

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Summary: This paper introduces a new local Gaussian spectral density that can be used to detect non-Gaussian traits and nonlinear dependencies in time series, particularly suitable for time series with asymmetries and nonlinear dependencies.

JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION (2022)

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Article Economics

The Locally Gaussian Partial Correlation

Hakon Otneim et al.

Summary: This article introduces a new measure of conditional dependence called the local Gaussian partial correlation (LGPC). Compared to traditional partial correlation coefficients, LGPC can better describe conditional dependence in a wide range of populations and has some useful and novel properties. LGPC can also be used to study departures from conditional independence in specific parts of the distribution.

JOURNAL OF BUSINESS & ECONOMIC STATISTICS (2022)

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Article Statistics & Probability

Statistical Dependence: Beyond Pearson's ρ

Dag Tjostheim et al.

Summary: This paper presents the most used measure of statistical dependence, Pearson's rho, and its shortcomings in different situations. It also provides an overview and comparison of several alternative methods.

STATISTICAL SCIENCE (2022)

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Article Computer Science, Theory & Methods