Laplace Periodogram for Time Series Analysis
By Ta‐Hsin Li. 2008
107 citations recorded by the source corpus.
Subfields: Cardiology and Cardiovascular Medicine, Economics and Econometrics, Signal Processing
View Paper: https://www.semanticscholar.org/paper/70f0e836d45955d3665891bb68beb698e4afe9da
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In Cardiology and Cardiovascular Medicine
In Economics and Econometrics
- Tobias Kley
- Stanislav Volgushev
- Holger Dette
- Marc Hallin
- Andreas Hagemann
- Stefan Birr
- Jushan Bai
- George Kapetanios
In Signal Processing
Citations in the corpus
- An Updated Literature Review of Distance Correlation and Its Applications to Time Series (2017, unknown): “They proposed to estimate the corresponding spectral densities associated with measures (29) and (30) via Laplace periodogram (Li, 2008).”
- Quantile Spectral Processes: Asymptotic Analysis and Inference (2014, unknown): “Li [38,39] does not consider asymptotics for smoothed versions of his quantile periodograms, while the asymptotic results in Hagemann [19] and Dette et al.”
- Quantile spectral analysis for locally stationary time series (2014, background): “, of the form Cov(I fX t;Tq t;T(˝ 1)g;I fX s;Tq s;T(˝ 2)g), where q t;T(˝ 1) and q s;T(˝ 2) stand for the ˝ 1-quantile of X t;T and the ˝ 2-quantile of X s;T, respectively, with ˝ 1;˝ 2 2(0;1); see Li (2008, 2012), Hagemann (2013), or Dette et al. (2015). Such covariances only depend on the bivariat”
- Robust Spectral Analysis (2011, methodology): “Li (2008, 2011) obtains robust spectral estimators via quantile regressions for harmonic regression models.”
- Quantile coherency: A general measure for dependence between cyclical economic variables (2015, unknown): “Li (2008) proposed an estimator for a weighted version of the quantile spectra, based on least absolute deviation regression, for the special case where τ 1 = τ 2 = 0 .”
- The Cross-Quantilogram: Measuring Quantile Dependence and Testing Directional Predictability between Time Series (2014, unknown): “Given random block lengths {Li}i∈N under the stationary bootstrap, define N = inf{i ∈ N : L1 + · · ·+ Li ≥ n}. Then, N is a stopping time with respect to {σ(L1, . . . , Li) : 1 ≤ i ≤ n}. In the following lemma, we present a moment inequality using ideas found in the literature on the sopped random w”