The Level-Based Stratified Sampling Plan
基于输出等值面的分层抽样方案AI 解读 ↓
← 返回论文列表与筛选
阅读说明
本页整理公开书目信息，不生成学术质量评分。AI 解读根据题名及所注明的摘要或原文片段生成，未完成全文核验，可能有误；具体假设、证明与结论请核对原文。摘要保留来源文本，未经模型改写。
DOI 首次登记不等于接收或发表日期。部分更正、评论等条目没有独立摘要；缺少可靠材料时保留待补状态。
引用量采用 OpenAlex 单条关联记录，不合计多个记录；关联记录可能包含正式发表版本，不等于此版本单独引用。缺失不视为零，引用指标不代表论文质量。
关注作者按书目中的完整姓名匹配，同名和姓名变体需人工辨别。相关论文先按共享细分方向和具体方法排列，再参考通用方法与发表日期。
分类依据与纠错
AI 根据所提供的论文材料归类：摘要研究计算机模拟的分层抽样设计，没有直接涉及所列分布效应、预测或其他计量细分。
反馈分类问题
正在核对关联版本…
代码、数据与补充材料
正在核对对应版本的资源…
关注这篇论文的作者
基于输出等值面的分层抽样方案
- 研究问题
- 当计算机模型运行昂贵而输入分布已知时，如何选择有限次运行的输入组合，以降低输出分布估计的抽样方差？
- 方法与思路
- 作者用输出恒定的等值面界定分层，研究相应抽样方案，并借助粗网格有限元模型近似构造细网格模型的抽样设计。
- 材料陈述的贡献
- 摘要称理想等值面分层在所讨论无偏抽样方案中方差最低，但构造需要已知解；近似解可用于形成可实施方案。
- 阅读关注点
- 应核对最低方差结论针对的估计目标和方案范围、各层样本配置，以及粗模型近似如何影响无偏性和实际方差。
- 阅读边界
- 依据版本未注明的 OpenAlex 索引摘要；不能推断刊本变化。理想方案依赖已知解，摘要未说明近似方案保留哪些最优性质。
原文摘要
If the probability distribution of the input variables to a system described by a computer code is known, the distribution function of the output variable can be obtained by computer simulations. With a complicated program, each simulation can take very long time. It thus is necessary to choose the combinations of the input parameters carefully to get as much information as possible with a small number of computer runs. Different methods (true random sampling, stratified sampling, Latin hypercube sampling, and updated Latin hypercube sampling) for choosing the input parameters are described in the literature. As a criteria for a good sampling plan, unbiased estimates and low mean squared error are used. By computer experiments, it has been shown that the sampling plans based on Latin hypercubes often have the smallest variance of the estimated output variable. In this article it is shown that a stratified sampling plan with strata defined by the surfaces in the sampling space where the output variable is constant has the lowest variance among all unbiased sampling plans. Unfortunately, it is possible to construct the sampling plan only if the solution is already available. However, an approximate sampling plan can be constructed if an approximate solution is known. In an application, it is shown how the results from a finite element method (FEM) model with a coarse element structure can be used to construct a sampling plan to be used with a FEM model with a finer element structure.