Estimation of trend in state-space models: asymptotic mean square error and rate of convergence
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Publication:1043710
DOI10.1214/08-AOS675zbMath1360.62452arXiv0911.3469OpenAlexW3103929726MaRDI QIDQ1043710
Robert H. Shumway, Prabir Burman
Publication date: 9 December 2009
Published in: The Annals of Statistics (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/0911.3469
Density estimation (62G07) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Asymptotic properties of nonparametric inference (62G20)
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Cites Work
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- Nonparametric curve estimation with time series errors
- ASP fits to multi-way layouts
- Large-sample inference for nonparametric regression with dependent errors
- State space modeling of long-memory processes
- Optimal global rates of convergence for nonparametric regression
- Nonlinear time series. Nonparametric and parametric methods
- Local polynomial fitting with long-memory, short-memory and antipersistent errors
- A unifying approach to some old and new theorems on distribution and clustering
- Toeplitz matrices, asymptotic linear algebra and functional analysis
- Approximate singular values of the fractional difference and summation operators
- Regression function estimation from dependent observations
- The Signal Extraction Approach to Nonlinear Regression and Spline Smoothing
- Matrix Analysis
- Nonparametric spline regression with autoregressive moving average errors
- Fixed-design regression for linear time series
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