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Computerized adaptive testing is becoming increasingly popular due to advancement of modern computer technology. It differs from the conventional standardized testing in that the selection of test items is tailored to individual examinee's…

Statistics Theory · Mathematics 2009-06-11 Hua-Hua Chang , Zhiliang Ying

We propose a general methodology of sequential locally optimal design of experiments for explicit or implicit nonlinear models, as they abound in chemical engineering and, in particular, in vapor-liquid equilibrium modeling. As a sequential…

Optimization and Control · Mathematics 2024-03-15 Martin Bubel , Jochen Schmid , Volodymyr Kozachynskyi , Erik Esche , Michael Bortz

Calibration of expensive simulation models involves an emulator based on simulation outputs generated across various parameter settings to replace the actual model. Noisy outputs of stochastic simulation models require many simulation…

Methodology · Statistics 2025-05-08 Özge Sürer

The unknown parameters of simulation models often need to be calibrated using observed data. When simulation models are expensive, calibration is usually carried out with an emulator. The effectiveness of the calibration process can be…

Computation · Statistics 2024-12-03 Özge Sürer , Stefan M. Wild

We consider likelihood-based two-step estimation of latent variable models, in which just the measurement model is estimated in the first step and the measurement parameters are then fixed at their estimated values in the second step where…

Methodology · Statistics 2025-08-26 Jouni Kuha , Zsuzsa Bakk

In this paper, we consider the problem of estimating parameters in a linear regression model. We propose a sequential learning procedure to determine the sample size for achieving a given small estimation risk, under the widely used…

Methodology · Statistics 2023-11-07 Jun Hu , Yan Zhuang , Shunan Zhao

Simulation models of critical systems often have parameters that need to be calibrated using observed data. For expensive simulation models, calibration is done using an emulator of the simulation model built on simulation output at…

Methodology · Statistics 2023-08-24 Özge Sürer , Matthew Plumlee , Stefan M. Wild

We propose a sequential design method aiming at the estimation of an extreme quantile based on a sample of dichotomic data corresponding to peaks over a given threshold. This study is motivated by an industrial challenge in material…

Methodology · Statistics 2020-04-06 Michel Broniatowski , Emilie Miranda

We consider the problem of sequential evaluation, in which an evaluator observes candidates in a sequence and assigns scores to these candidates in an online, irrevocable fashion. Motivated by the psychology literature that has studied…

Machine Learning · Statistics 2023-11-20 Jingyan Wang , Ashwin Pananjady

Researchers faced with a sequence of candidate model specifications must often choose the best specification that does not violate a testable identification assumption. One option in this scenario is sequential specification tests:…

Methodology · Statistics 2023-07-25 Adam C. Sales

In computerized adaptive testing (CAT), items (questions) are selected in real time based on the already observed responses, so that the ability of the examinee can be estimated as accurately as possible. This is typically formulated as a…

Statistics Theory · Mathematics 2015-01-08 Shiyu Wang , Georgios Fellouris , Hua-Hua Chang

Traditional accelerated life test plans are typically based on optimizing the C-optimality for minimizing the variance of an interested quantile of the lifetime distribution. The traditional methods rely on some specified planning values…

Applications · Statistics 2018-12-04 Lu Lu , I-Chen Lee , Yili Hong

Selecting input variables or design points for statistical models has been of great interest in adaptive design and active learning. Motivated by two scientific examples, this paper presents a strategy of selecting the design points for a…

Machine Learning · Statistics 2021-02-12 Chiwoo Park , Peihua Qiu , Jennifer Carpena-Núñez , Rahul Rao , Michael Susner , Benji Maruyama

A two-stage batch estimation algorithm for solving a class of nonlinear, static parameter estimation problems that appear in aerospace engineering applications is proposed. It is shown how these problems can be recast into a form suitable…

Signal Processing · Electrical Eng. & Systems 2020-02-18 Kerry Sun , Demoz Gebre-Egziabher

In this study, we demonstrate a sequential experimental design for spectral measurements by active learning using parametric models as predictors. In spectral measurements, it is necessary to reduce the measurement time because of sample…

Machine Learning · Computer Science 2023-05-15 Tomohiro Nabika , Kenji Nagata , Shun Katakami , Masaichiro Mizumaki , Masato Okada

Due to ethical and economical reasons, sequential single-arm trial designs are used for assessing the therapeutic efficacy of new treatments in phase II trials. Simon's 2-stage design and Lan-DeMets' $\alpha$-spending function method with…

Methodology · Statistics 2023-03-31 Tasuku Inao , Isao Yokota

In standardized educational testing, test items are reused in multiple test administrations. To ensure the validity of test scores, the psychometric properties of items should remain unchanged over time. In this paper, we consider the…

Applications · Statistics 2021-10-26 Yunxiao Chen , Yi-Hsuan Lee , Xiaoou Li

Multi-stage (designed) procedures, obtained by splitting the sampling budget suitably across stages, and designing the sampling at a particular stage based on information about the parameter obtained from previous stages, are often…

Methodology · Statistics 2014-01-08 Atul Mallik , Moulinath Banerjee , George Michailidis

We propose and analyze sequential design methods for the problem of ranking several response surfaces. Namely, given $L \ge 2$ response surfaces over a continuous input space $\cal X$, the aim is to efficiently find the index of the minimal…

Machine Learning · Statistics 2017-10-17 Ruimeng Hu , Mike Ludkovski

A sequential quadratic programming method is designed for solving general smooth nonlinear stochastic optimization problems subject to expectation equality constraints. We consider the setting where the objective and constraint function…

Optimization and Control · Mathematics 2026-03-17 Haoming Shen , Yang Zeng , Baoyu Zhou
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