Using bimodal kernel for inference in nonparametric regression with correlated errors
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Publication:1021849
DOI10.1016/j.jmva.2008.12.012zbMath1162.62033OpenAlexW1981723612MaRDI QIDQ1021849
Byeong U. Park, Chiho Kim, Tae Yoon Kim, Myung-Sang Moon
Publication date: 9 June 2009
Published in: Journal of Multivariate Analysis (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/j.jmva.2008.12.012
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Cites Work
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- Practically applicable central limit theorem for spatial statistics
- Bandwidth selection for kernel estimate with correlated noise
- Comparison of two bandwidth selectors with dependent errors
- Nonparametric regression with correlated errors.
- On bandwidth choice in nonparametric regression with both short- and long-range dependent errors
- A framework to understand the asymptotic properties of kriging and splines
- Nonparametric detection of correlated errors
- A Simple Estimator of Error Correlation in Non-parametric Regression Models
- Moment inequalities for mixing sequences of random variables
- How Far Are Automatically Chosen Regression Smoothing Parameters From Their Optimum?
- Choice of bandwidth for kernel regression when residuals are correlated
- Using Difference-Based Methods for Inference in Nonparametric Regression with Time Series Errors
- Plug-in bandwidth selector for local polynomial regression estimator with correlated errors
- Smoothing parameter selection methods for nonparametric regression with spatially correlated errors
