搜索结果: 1-5 共查到“非参数统计 Density estimation”相关记录5条 . 查询时间(0.125 秒)
Asymptotic Equivalence of Spectral Density Estimation and Gaussian White Noise
Stationary Gaussian process spectral density Sobolev classes Le Cam distance asymptotic equivalence Whittle likelihood log-periodogram regression nonparametric Gaussian scale model signal in Gaussian white noise
2015/8/25
We consider the statistical experiment given by a sample y(1), . . . , y(n) of a stationary Gaussian process with an unknown smooth spectral density f. Asymptotic equivalence, in the sense of Le Cam’s...
The Asymptotic Minimax Constant for Sup-Norm Loss in Nonparametric Density Estimation
Density estimation exact constant optimal recovery uniform norm risk white noise
2015/8/25
We develop the exact constant of the risk asymptotics in the uniform norm for density estimation. This constant has first been found for nonparametric regression and for signal estimation in Gaussian ...
ASYMPTOTIC EQUIVALENCE OF DENSITY ESTIMATION AND GAUSSIAN WHITE NOISE
ASYMPTOTIC EQUIVALENCE DENSITY ESTIMATION GAUSSIAN WHITE NOISE
2015/8/25
Signal recovery in Gaussian white noise with variance tending to zero has served for some time as a representative model for nonparametric curve estimation, having all the essential traits in a pure f...
Asymptotic Equivalence of Density Estimation and Gaussian White Noise
Asymptotic Equivalence Density Estimation Gaussian White Noise
2015/8/25
Signal recovery in Gaussian white noise with variance tending to zero has served for some time as a representative model for nonparametric curve estimation, having all the essential traits in a pure f...
Non-Parametric Maximum Likelihood Density Estimation and Simulation-Based Minimum Distance Estimators
Non-Parametric Maximum Likelihood Density Estimation Simulation-Based Minimum Distance Estimators
2011/2/22
Indirect inference estimators (i.e., simulation-based minimum distance estimators) in a
parametric model that are based on auxiliary non-parametric maximum likelihood density
estimators are shown to...
