Inference on power law spatial trends
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Publication:418245
DOI10.3150/10-BEJ349zbMath1238.62106arXiv1205.2508MaRDI QIDQ418245
Publication date: 28 May 2012
Published in: Bernoulli (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/1205.2508
Asymptotic properties of parametric estimators (62F12) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Asymptotic distribution theory in statistics (62E20)
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Cites Work
- Unnamed Item
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- Local linear spatial quantile regression
- Estimation of the parameters of linear time series models subject to nonlinear restrictions
- Gaussian maximum likelihood estimation for ARMA models. II: Spatial processes
- Multiple local Whittle estimation in stationary systems
- On estimation of a regression model with long-memory stationary errors
- Asymptotic theory of nonlinear least squares estimation
- Nonlinear log-periodogram regression for perturbed fractional processes
- Gaussian estimation of parametric spectral density with unknown pole
- Exploring spatial nonlinearity using additive approximation
- Modified Whittle estimation of multilateral models on a lattice
- Estimation in semiparametric spatial regression
- Statistical spatial series modelling II: Some further results on unilateral lattice processes
- Statistical spatial series modelling
- Asymptotic Properties of Non-Linear Least Squares Estimators
- The Consistency of Nonlinear Regressions
- Density estimation for spatial linear processes