Data analysis tools for uncertainty quantification of inverse problems

Data analysis tools for uncertainty quantification of inverse problems
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用于逆问题不确定性量化的数据分析工具

DOI:
10.1088/0266-5611/27/4/045001
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发表时间:
2011
期刊:
影响因子:
2.1
通讯作者:
Ping Ma
Ping Ma
中科院分区:
数学2区
文献类型:
--
作者:
Luis Tenorio;Fredrik Andersson;M. V. Hoop;Ping Ma

文献摘要

被引文献

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我们提出了探索性的数据分析方法,以评估反演估计使用的例子的基础上,102-和101-正则化。这些方法可用于揭示系统误差的存在,如偏差和离散化效应,或验证分析中使用的统计模型的假设。该方法包括一个大矩阵的随机估计的性能,置信区间和界限的偏差,resternation方法模型验证和建设的训练集的功能与控制的局部正则性的界限。
We present exploratory data analysis methods to assess inversion estimates using examples based on ℓ2- and ℓ1-regularization. These methods can be used to reveal the presence of systematic errors such as bias and discretization effects, or to validate assumptions made on the statistical model used in the analysis. The methods include bounds on the performance of randomized estimators of a large matrix, confidence intervals and bounds for the bias, resampling methods for model validation and construction of training sets of functions with controlled local regularity.