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AI 根据所提供的论文材料归类：摘要聚焦昂贵模拟器的逆问题与水文校准，时间序列输出本身不足以确定所列经济计量细分方向。

splinetime seriesestimation

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Solving an Inverse Problem for Time Series Valued Computer Simulators via Multiple Contour Estimation

Pritam Ranjan · Joseph Resch · Abhyuday Mandal首次提交 2022-11-02 · 修订 2022-11-02 · v1arXiv预印本

通过多重等值轮廓估计求解时间序列输出模拟器的逆问题AI 解读 ↓

时间序列核、筛与局部多项式

关联记录被引 1 次 ↗OpenAlex · 核验 2026-09-30

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arXiv

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arXiv：2211.01119 · v1

首次提交：2022-11-02 · 最近修订：2022-11-02

原站分类：stat.ME / stat.CO

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关注这篇论文的作者

Pritam Ranjan

Joseph Resch

Abhyuday Mandal

AI 解读 · 基于可核验材料

通过多重等值轮廓估计求解时间序列输出模拟器的逆问题

研究问题: 当计算机模拟器运行昂贵且输出整条时间序列时，如何高效寻找匹配目标序列的输入，并量化逆解的不确定性？
方法与思路: 作者用回归样条选取少量最优时间节点，再在这些节点分别进行标量输出的等值轮廓估计，形成 MSCE 方法。
材料陈述的贡献: 摘要称方法支持逆解的不确定性量化，并通过测试函数模拟器与美国佐治亚州雅典的降雨径流模型进行性能比较。
阅读关注点: 应核对时间节点的选择准则、多个标量逆问题如何形成共同解、节点间拟合误差，以及不确定性量化覆盖哪些来源。
阅读边界: 这是 arXiv 预印本，同行评审与期刊接收均未核实；摘要未说明逆解唯一性、计算成本和比较数值，不能判断整体优势。

GPT-6.1 Sol · 高 · 2026-10-03

原文摘要

Computer simulators are often used as a substitute of complex real-life phenomena which are either expensive or infeasible to experiment with. This paper focuses on how to efficiently solve the inverse problem for an expensive to evaluate time series valued computer simulator. The research is motivated by a hydrological simulator which has to be tuned for generating realistic rainfall-runoff measurements in Athens, Georgia, USA. Assuming that the simulator returns g(x,t) over L time points for a given input x, the proposed methodology begins with a careful construction of a discretization (time-) point set (DPS) of size $k << L$ , achieved by adopting a regression spline approximation of the target response series at k optimal knots locations $\{t^*_1, t^*_2, ..., t^*_k\}$ . Subsequently, we solve k scalar valued inverse problems for simulator $g(x,t^*_j)$ via the contour estimation method. The proposed approach, named MSCE, also facilitates the uncertainty quantification of the inverse solution. Extensive simulation study is used to demonstrate the performance comparison of the proposed method with the popular competitors for several test-function based computer simulators and a real-life rainfall-runoff measurement model.Computer simulators are often used as a substitute of complex real-life phenomena which are either expensive or infeasible to experiment with. This paper focuses on how to efficiently solve the inverse problem for an expensive to evaluate time series valued computer simulator. The research is motivated by a hydrological simulator which has to be tuned for generating realistic rainfall-runoff measurements in Athens, Georgia, USA. Assuming that the simulator returns g(x,t) over L time points for a given input x, the proposed methodology begins with a careful construction of a discretization (time-) point set (DPS) of size $k << L$, achieved by adopting a regression spline approximation of the target response series at k optimal knots locations $\{t^*_1, t^*_2, ..., t^*_k\}$. Subsequently, we solve k scalar valued inverse problems for simulator $g(x,t^*_j)$ via the contour estimation method. The proposed approach, named MSCE, also facilitates the uncertainty quantification of the inverse solution. Extensive simulation study is used to demonstrate the performance comparison of the proposed method with the popular competitors for several test-function based computer simulators and a real-life rainfall-runoff measurement model.

摘要来源：arXiv

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