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논문 기본 정보
- 자료유형
- 학술저널
- 저자정보
- 발행연도
- 2004.6
- 수록면
- 467 - 476 (10page)
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초록· 키워드
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Recently, an approximation of a wavelet series has been developed in the analyses of an unknown function. Most of articles have been studied on thresholding and shrinkage methods for its wavelet coefficients based on (non)parametric and Bayesian methods when the sample size is considered as a maximum resolution in wavelet series. In this paper, regardless of the sample size, we are focusing only on the choice of a maximum resolution in wavelet series. We propose a Bayesian approach to the choice of a maximum resolution based on the linear combination of the wavelet basis functions.
목차
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참고문헌 (4)
참고문헌 신청
[학술지(정기간행물)] - / 1973 / Bayesian Inference in Statistical Analysis
[학술지(정기간행물)] - I / 1988 / Ten Lectures on Wavelets Series in Applied Mathematics
[학술지(정기간행물)] - Mller P / 1999 / MCMC Methods in Wavelet Shrinkage: Non-Equally Spaced Regression, Density and Spectral Density Estimation" in Bayesian Inference in Wavelet Based Models, eds
[학술지(정기간행물)] - Smith M / 1997 / A Bayesian Approach to Nonparametric Bivariate Regression 92 : 1522 ~ 1535
[학술지(정기간행물)] - I / 1988 / Ten Lectures on Wavelets Series in Applied Mathematics
[학술지(정기간행물)] - Mller P / 1999 / MCMC Methods in Wavelet Shrinkage: Non-Equally Spaced Regression, Density and Spectral Density Estimation" in Bayesian Inference in Wavelet Based Models, eds
[학술지(정기간행물)] - Smith M / 1997 / A Bayesian Approach to Nonparametric Bivariate Regression 92 : 1522 ~ 1535
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