Methods › Sequential › Time Series Analysis › DPCCA

Detrended Partial-Cross-Correlation Analysis

DPCCA

6 papers tagged archive 2025-07-28

Introduced by Naiming Yuan et al. in Detrended Partial-Cross-Correlation Analysis: A New Method for Analyzing Correlations in Complex System

archive 2025-07-28 Description, source and code snippet are the archive's method entry.

Based on detrended cross-correlation analysis (DCCA), this method is improved by including partial-correlation technique, which can be applied to quantify the relations of two non-stationary signals (with influences of other signals removed) on different time scales.

PaperSource

Papers archive 2025-07-28

6 shown of 6, newest first. Repository counts are the archive's code-links table. A Syntology line states what Syntology ran from that paper's harvested code; it is per sample and not a correctness claim.

Tasks archive 2025-07-28

4 tasks the archive attaches to papers tagged with this method, by distinct papers. A task without a page in the catalog is plain text.

TaskPapers
Time Series Analysis3
Time Series2
Representation Learning1
Trajectory Modeling1

Usage over time archive 2025-07-28

Papers per year tagged with DPCCA: 2015 to 2025, peak 3 3 0 2015: 3 papers 2015 2016: 0 papers 2016 2017: 0 papers 2017 2018: 0 papers 2018 2019: 0 papers 2019 2020: 0 papers 2020 2021: 1 paper 2021 2022: 0 papers 2022 2023: 1 paper 2023 2024: 0 papers 2024 2025: 1 paper 2025
Papers per year the archive tags with this method, by the paper's archive date (6 dated). Bars are counts, not a trend claim.

Components: the archive holds no method-to-method composition, so PwC's Components table cannot be rebuilt; the Papers list carries no Results column for the same reason (the archive does not join its leaderboard rows to method tags).

Categories archive 2025-07-28

Time Series Analysis

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