Estimating the Mean Direction of Strongly Dependent Circular Time Series
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Publication:5111842
DOI10.1111/jtsa.12500zbMath1445.62218OpenAlexW2967271878WikidataQ127392579 ScholiaQ127392579MaRDI QIDQ5111842
Publication date: 27 May 2020
Published in: Journal of Time Series Analysis (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1111/jtsa.12500
Directional data; spatial statistics (62H11) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Applications of statistics to environmental and related topics (62P12) Nonparametric tolerance and confidence regions (62G15) Meteorology and atmospheric physics (86A10)
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On nonparametric regression for bivariate circular long-memory time series ⋮ Recent advances in directional statistics
Cites Work
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- Kernel density estimation with spherical data
- Asymptotic properties of the LSE in a regression model with long-memory stationary errors
- On estimation of a regression model with long-memory stationary errors
- Multiple Wiener-Ito integrals. With applications to limit theorems
- The analysis of directional time series: Applications to wind speed and direction. (Based on the author's thesis, Univ. of Western Australia in Perth)
- Broadband log-periodogram regression of time series with long-range dependence
- The FEXP estimator for potentially non-stationary linear time series.
- Log-periodogram regression of time series with long range dependence
- Gaussian semiparametric estimation of long range dependence
- Data Driven Order Selection for Projection Estimator of the Spectral Density of Time Series with Long Range Dependence
- Topics in Circular Statistics
- Broadband Semiparametric Estimation of the Memory Parameter of a Long‐Memory Time Series Using Fractional Exponential Models
- Model Selection for Broadband Semiparametric Estimation of Long Memory in Time Series
- On trend estimation under monotone Gaussian subordination with long-memory: application to fossil pollen series
- Asymptotic normality of wavelet estimators of the memory parameter for linear processes
- Statistical Analysis of Circular Data
- THE ESTIMATION AND APPLICATION OF LONG MEMORY TIME SERIES MODELS
- Bivariate models for dependence of angular observations and a related Markov process
- Weak convergence to fractional brownian motion and to the rosenblatt process
- Some limit theorems for partial sums of quadratic forms in stationary Gaussian variables
- Some Angular-Linear Distributions and Related Regression Models
- Convergence of integrated processes of arbitrary Hermite rank
- Non-central limit theorems for non-linear functional of Gaussian fields
- Fitting long-memory models by generalized linear regression
- Block Bootstrap for the Empirical Process of Long‐Range Dependent Data
- A Markov Process for Circular Data
- Long-Memory Processes
- Modeling Space and Space-Time Directional Data Using Projected Gaussian Processes
- Broadband semi-parametric estimation of long-memory time series by fractional exponential models
- Non‐parametric smoothing and prediction for nonlinear circular time series
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