Wasserstein autoregressive models for density time series
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Publication:5030950
DOI10.1111/jtsa.12590zbMath1493.62182arXiv2006.12640OpenAlexW3154256386MaRDI QIDQ5030950
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Publication date: 18 February 2022
Published in: Journal of Time Series Analysis (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/2006.12640
Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Asymptotic properties of nonparametric inference (62G20) Nonparametric estimation (62G05)
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Cites Work
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- A Mathematical Theory of Communication
- Simplicial principal component analysis for density functions in Bayes spaces
- Amplitude and phase variation of point processes
- Inference for functional data with applications
- Geodesic PCA in the Wasserstein space by convex PCA
- Time series: theory and methods.
- Linear processes in function spaces. Theory and applications
- Strictly stationary solutions of multivariate ARMA equations with i.i.d. noise
- Two sample inference for the second-order property of temporally dependent functional data
- Strictly stationary solutions of ARMA equations in Banach spaces
- Hilbert space of probability density functions based on Aitchison geometry
- Testing stationarity of functional time series
- Wasserstein \(F\)-tests and confidence bands for the Fréchet regression of density response curves
- Strictly stationary solutions of autoregressive moving average equations
- Quantile Function on Scalar Regression Analysis for Distributional Data
- Inference for Density Families Using Functional Principal Component Analysis
- Introduction to Functional Data Analysis
- Detecting Changes in the Mean of Functional Observations
- Wasserstein covariance for multiple random densities
- An Invitation to Statistics in Wasserstein Space
- Localized Realized Volatility Modeling
- On Information and Sufficiency
- Functional data analysis for density functions by transformation to a Hilbert space
