This is page 1 Printer Opaque this Empirical Bayesian Spatial Prediction Using Wavelets(18)

ABSTRACT Wavelet shrinkage methods, introduced by Donoho and Johnstone

14

Hsin-Cheng Huang, Noel Cressie1.0 0.2 0.4 0.6 0.8

VisuShrink

SureShrink

DecompShrink

FIGURE 4. Boxplots of MSE performance of the\blocks" signal using various wavelet shrinkage techniques based on 100 replications (n= 2048, SD(S )= 7,= 1).8 2 4 6

VisuShrink

SureShrink

DecompShrink

FIGURE 5. Boxplots of MSE performance of the AR(1) signal using various wavelet shrinkage techniques based on 100 replications (n= 2048, SD(S )= 7,= 1).

Based on the random variation in the stochastic signal and noise, 100 repli?^ cations of Y were obtained. Each replicate gives a MSE S . Figure 4, Figure 5, and Figure 6 show the boxplots of these MSE values for the\blocks", AR(1), and\blocks+ AR(1) signals, respectively, based on the 100 replications. The simulation results are also summarized in Table 1 by averaging over the 100 replications for each shrinkage method and for each test signal. From Figure 4, Figure 5, Figure 6, and Table 1, we see that the MSE values obtained from the DecompShrink method have a distribution that is closer to zero than those from the other two methods. It is quite clear that the DecompShrink method is superior to the VisuShrink and the SureShrink methods for recovery of these three signals. Table 2 shows the estimation of the noise parameter for n= 2048,

ABSTRACT Wavelet shrinkage methods, introduced by Donoho and Johnstone

VisuShrinkSureShrinkDecompShrink

搜索“diyifanwen.net”或“第一范文网”即可找到本站免费阅读全部范文。收藏本站方便下次阅读，第一范文网，提供最新工程科技This is page 1 Printer Opaque this Empirical Bayesian Spatial Prediction Using Wavelets(18)全文阅读和word下载服务。