Fourier Analysis of Irregularly Spaced Data onRd
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Publication:3551038
DOI10.1111/j.1467-9868.2008.00685.xzbMath1231.62169OpenAlexW2101011525MaRDI QIDQ3551038
Yoshihiro Yajima, Yasumasa Matsuda
Publication date: 8 April 2010
Published in: Journal of the Royal Statistical Society Series B: Statistical Methodology (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1111/j.1467-9868.2008.00685.x
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Cites Work
- Unnamed Item
- Unnamed Item
- Large sample optimality of least squares cross-validation in density estimation
- A central limit theorem for parameter estimation in stationary vector time series and its application to models for a signal observed with noise
- Fixed-Domain Asymptotics for Spatial Periodograms
- Edge effects and efficient parameter estimation for stationary random fields
- Topics in Advanced Econometrics
- Nonseparable, Stationary Covariance Functions for Space–Time Data
- Classes of Nonseparable, Spatio-Temporal Stationary Covariance Functions
- Approximating Likelihoods for Large Spatial Data Sets
- Band Spectrum Regression
- Statistics for Spatial Data
- Approximate Likelihood for Large Irregularly Spaced Spatial Data
- Asymptotic properties of least-squares estimates of parameters of the spectrum of a stationary non-deterministic time-series
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