M-estimatorsrobust estimationinfluence functionThis paper provides a summary of the influence function approach to robust estimation of parametric models. Hampel's optimality results for M-estimators with a bounded influence function is generalized to allow for arbitrary choices of the asymptotic efficiency...
In the proposed diffusion model, the diffusivity function is replaced by robust M-estimators weight function and the modulus of gradient in a diffusivity function is substituted by the average of local gradient in a 3x3 window. The proposed method is tested on a number of benchmarks and ...
M-estimators思想就是在每一个损失项上加个robust filtering kernel,求解似然函数最小值求得解:\theta^*,具体实现方式:采用每次迭代修改权重求最小二乘的方法。第一步:根据前一次迭代(k-1)的结果得到第k次的权重:w_{i}^{k}(i表示损失分量(点数))第二步:将权重应用于每个分量,进行第k次优化得到\theta^k ...
Robust prediction limits based on M-estimatorsRobust prediction limits based on M-estimatorsBiasInfluence functionPredictionRobustnessScale-regression modelWe discuss a robust solution to the problem of prediction. Extending Barndorff-Nielsen and Cox [1996. Prediction and asymptotics. Bernoulli 2, 319–340...
Robust M-estimation procedures for relevant parameters of discriminant analysis are developed. The optimal robust M-estimators for discriminant function coefficients, Mahalanobis'$\Delta ^{2}$and misclassification probabilities are obtained. These optimal robust estimators do not generally have breakdown point...
关键词: image processing - denoising technique - nonlocal-means filter - robust M-estimators DOI: 10.1007/s11390-010-9351-z 被引量: 20 年份: 2010 收藏 引用 批量引用 报错 分享 全部来源 免费下载 求助全文 Semantic Scholar (全网免费下载) dx.doi.org alljournals.cn (全网免费下载) ResearchGate...
robust regression and M-estimators Use other criteria(loss) than least squares for heavy tail data points. This class ofestimatorscan be regarded as ageneralizationof maximum-likelihoodestimation, hence the term “M”-estimation(Max likelihood):\\ \hat{\beta}=\min \sum_{i=1}^n \rho(y_i-...
In the case of asymmetric contamination it may be superior than Huber''s M-estimatorsdoi:10.1080/03610929608831858MarkatouMarianthiMarcel Dekker, Inc.Communications in StatisticsMarkatou, M. (1996). Robust statistical inference: Weighted likelihood or usual M -estimation? Communications in Statistics: ...
robust M-estimator function rather than the exponential function for its weight calculation.Here the filter output at each pixel is the weighted average of pixels with surrounding neighborhoods using the chosen robust M-estimator function.The main direction of this paper is to identify the best ...
关键词: image processing denoising technique nonlocal-means filter robust M-estimators DOI: 10.1007/s11390-010-9351-z 被引量: 50 年份: 2010 收藏 引用 批量引用 报错 分享 全部来源 免费下载 求助全文 Springer 万方 掌桥科研 知网 维普网 查看更多 相似文献 参考文献 引证文献...