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Relevant bibliographies by topics / Computer-Intensive Statistics

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Academic literature on the topic 'Computer-Intensive Statistics'

Author: Grafiati

Published: 5 June 2025

Last updated: 2 August 2025

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Journal articles on the topic "Computer-Intensive Statistics"

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Ghosh, Subir. "Computer Intensive Methods in Statistics." Technometrics 62, no. 3 (2020): 415. http://dx.doi.org/10.1080/00401706.2020.1783946.

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Sunil, K. Sapra. "Computer-Intensive Statistics: A Promising Interplay between Statistics and Computer Science." Advances in Computer Sciences 1, no. 3 (2018): 1–2. https://doi.org/10.31021/acs.20181113.

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<strong>Editorial</strong> Statistics and computer science have grown as separate disciplines with little interaction for the past several decades. This however, has changed radically in recent years with the availability of massive and complex datasets in medicine, social media, and physical sciences. The statistical techniques developed for regular datasets simply cannot be scaled to meet the challenges of big data, notably the computational and statistical curses of dimensionality. The dire need to meet the challenges of big data has led to the development of statistical learning, machine l

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Schmerling, Siegfried. "Computer intensive methods in statistics. Series statistics and computing." Computational Statistics & Data Analysis 17, no. 5 (1994): 602–3. http://dx.doi.org/10.1016/0167-9473(94)90152-x.

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Ziegel, Eric R., and H. Rieder. "Robust Statistics, Data Analysis, and Computer Intensive Methods." Technometrics 39, no. 2 (1997): 238. http://dx.doi.org/10.2307/1270930.

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Militino, Ana Fernández. "Robust statistics, data analysis, and computer intensive methods." Computational Statistics & Data Analysis 24, no. 3 (1997): 373–74. http://dx.doi.org/10.1016/s0167-9473(97)87029-6.

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McElroy, Tucker, and Dimitris N. Politis. "Computer-intensive rate estimation, diverging statistics and scanning." Annals of Statistics 35, no. 4 (2007): 1827–48. http://dx.doi.org/10.1214/009053607000000064.

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Ludbrook, John. "ISSUES IN BIOMEDICAL STATISTICS: COMPARING MEANS BY COMPUTER-INTENSIVE TESTS." ANZ Journal of Surgery 65, no. 11 (1995): 812–19. http://dx.doi.org/10.1111/j.1445-2197.1995.tb00567.x.

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Flack, Virginia F., and Eric W. Noreen. "Computer Intensive Methods for Testing Hypotheses: An Introduction." Journal of the American Statistical Association 85, no. 410 (1990): 599. http://dx.doi.org/10.2307/2289819.

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Cover, K. A., and T. E. Unny. "APPLICATION OF COMPUTER INTENSIVE STATISTICS TO PARAMETER UNCERTAINTY IN STREAMFLOW SYNTHESIS." Journal of the American Water Resources Association 22, no. 3 (1986): 495–507. http://dx.doi.org/10.1111/j.1752-1688.1986.tb01905.x.

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Worton, B. J., and J. S. U. Hjorth. "Computer Intensive Statistical Methods: Validation Model Selection and Bootstrap." Journal of the Royal Statistical Society. Series A (Statistics in Society) 157, no. 3 (1994): 504. http://dx.doi.org/10.2307/2983538.

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Dissertations / Theses on the topic "Computer-Intensive Statistics"

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Karlsson, Faronius Håkan. "On the Implementation of Computer Intensive Methods in Linear Normal Models." Thesis, Uppsala universitet, Tillämpad matematik och statistik, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-447013.

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Meintjes, M. M. (Maria Magdalena). "Evaluating the properties of sensory tests using computer intensive and biplot methodologies." Thesis, Stellenbosch : Stellenbosch University, 2007. http://hdl.handle.net/10019.1/20881.

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Assignment (MComm)--University of Stellenbosch, 2007.<br>ENGLISH ABSTRACT: This study is the result of part-time work done at a product development centre. The organisation extensively makes use of trained panels in sensory trials designed to asses the quality of its product. Although standard statistical procedures are used for analysing the results arising from these trials, circumstances necessitate deviations from the prescribed protocols. Therefore the validity of conclusions drawn as a result of these testing procedures might be questionable. This assignment deals with these questions.

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Marshall, Laura. "Statistical developments for understanding anthropogenic impacts on marine ecosystems." Thesis, University of St Andrews, 2012. http://hdl.handle.net/10023/3172.

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Over the past decades technological developments have both changed and increased human in influence on the marine environment. We now have greater potential than ever before to introduce disturbance and deplete marine resources. Two of the issues currently under public scrutiny are the exploitation of fish stocks worldwide and levels of anthropogenic noise in the marine environment. The aim of this thesis is to investigate and develop novel analyses and simulations to provide additional insight into some of the challenges facing the marine ecosystem today. These methodologies will improve the

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Chykeyuk, Kiryl. "Analysis of 3D echocardiography." Thesis, University of Oxford, 2014. http://ora.ox.ac.uk/objects/uuid:823cd243-5d48-4ecc-90e7-f56d49145be8.

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Heart disease is the major cause of death in the developed world. Due to its fast, portable, low-cost and harmless way of imaging the heart, echocardiography has become the most frequent tool for diagnosis of cardiac function in clinical routine. However, visual assessment of heart function from echocardiography is challenging, highly operatordependant and is subject to intra- and inter observer errors. Therefore, development of automated methods for echocardiography analysis is important towards accurate assessment of cardiac function. In this thesis we develop new ways to model echocardiogra

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Krohn, Jonathan Jacob Pastushchyn. "Genes contributing to variation in fear-related behaviour." Thesis, University of Oxford, 2013. http://ora.ox.ac.uk/objects/uuid:1e8e40bd-9a98-405f-9463-e9423f0a60ca.

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Anxiety and depression are highly prevalent diseases with common heritable elements, but the particular genetic mechanisms and biological pathways underlying them are poorly understood. Part of the challenge in understanding the genetic basis of these disorders is that they are polygenic and often context-dependent. In my thesis, I apply a series of modern statistical tools to ascertain some of the myriad genetic and environmental factors that underlie fear-related behaviours in nearly two thousand heterogeneous stock mice, which serve as animal models of anxiety and depression. Using a Bayesi

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Mayaud, Louis. "Prediction of mortality in septic patients with hypotension." Thesis, University of Oxford, 2014. http://ora.ox.ac.uk/objects/uuid:55a57418-de16-4932-8a42-af56bd380056.

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Sepsis remains the second largest killer in the Intensive Care Unit (ICU), giving rise to a significant economic burden ($17b per annum in the US, 0.3% of the gross domestic product). The aim of the work described in this thesis is to improve the estimation of severity in this population, with a view to improving the allocation of resources. A cohort of 2,143 adult patients with sepsis and hypotension was identified from the MIMIC-II database (v2.26). The implementation of state-of-the-art models confirms the superiority of the APACHE-IV model (AUC=73.3%) for mortality prediction using ICU adm

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Ramraj, Varun. "Exploiting whole-PDB analysis in novel bioinformatics applications." Thesis, University of Oxford, 2014. http://ora.ox.ac.uk/objects/uuid:6c59c813-2a4c-440c-940b-d334c02dd075.

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The Protein Data Bank (PDB) is the definitive electronic repository for experimentally-derived protein structures, composed mainly of those determined by X-ray crystallography. Approximately 200 new structures are added weekly to the PDB, and at the time of writing, it contains approximately 97,000 structures. This represents an expanding wealth of high-quality information but there seem to be few bioinformatics tools that consider and analyse these data as an ensemble. This thesis explores the development of three efficient, fast algorithms and software implementations to study protein struct

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Human, Schalk William. "Univariate parametric and nonparametric statistical quality control techniques with estimated process parameters." Thesis, 2009. http://hdl.handle.net/2263/28772.

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Chapter 1 gives a brief introduction to statistical quality control (SQC) and provides background information regarding the research conducted in this thesis. We begin Chapter 2 with the design of Shewhart-type Phase I S2, S and R control charts for the situation when the mean and the variance are both unknown and are estimated on the basis of m independent rational subgroups each of size n available from a normally distributed process. The derivations recognize that in Phase I (with unknown parameters) the signaling events are dependent and that more than one comparison is made against the sa

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Faisal, Muhammad, Andy J. Scally, R. Howes, K. Beatson, D. Richardson, and Mohammed A. Mohammed. "A comparison of logistic regression models with alternative machine learning methods to predict the risk of in-hospital mortality in emergency medical admissions via external validation." 2018. http://hdl.handle.net/10454/16623.

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Yes<br>We compare the performance of logistic regression with several alternative machine learning methods to estimate the risk of death for patients following an emergency admission to hospital based on the patients’ first blood test results and physiological measurements using an external validation approach. We trained and tested each model using data from one hospital (n=24696) and compared the performance of these models in data from another hospital (n=13477). We used two performance measures – the calibration slope and area under the curve (AUC). The logistic model performed reasonably

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Books on the topic "Computer-Intensive Statistics"

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Wolfgang, Härdle, and Simar Léopold, eds. Computer intensive methods in statistics. Physica- Verlag, 1993.

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Härdle, Wolfgang, and Léopold Simar, eds. Computer Intensive Methods in Statistics. Physica-Verlag HD, 1993. http://dx.doi.org/10.1007/978-3-642-52468-4.

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Rieder, Helmut, ed. Robust Statistics, Data Analysis, and Computer Intensive Methods. Springer New York, 1996. http://dx.doi.org/10.1007/978-1-4612-2380-1.

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J, Huber Peter, and Rieder Helmut, eds. Robust statistics, data analysis, and computer intensive methods: In honor of Peter Huber's 60th birthday. Springer, 1996.

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Noreen, Eric W. Computer-intensive methods for testing hypotheses: An introduction. Wiley, 1989.

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Zwanzig, Silvelyn, and Behrang Mahjani. Computer Intensive Methods in Statistics. Taylor & Francis Group, 2019.

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Zwanzig, Silvelyn, and Behrang Mahjani. Computer Intensive Methods in Statistics. Chapman and Hall/CRC, 2019. http://dx.doi.org/10.1201/9780429202322.

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Zwanzig, Silvelyn, and Behrang Mahjani. Computer Intensive Methods in Statistics. Taylor & Francis Group, 2019.

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Härdle, Wolfgang, and Léopold Simar. Computer Intensive Methods in Statistics. Physica, 2014.

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Härdle, Wolfgang, and Léopold Simar. Computer Intensive Methods in Statistics. Physica-Verlag, 2013.

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Book chapters on the topic "Computer-Intensive Statistics"

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Davison, A. C., and D. V. Hinkley. "Computer-Intensive Statistical Methods." In Computational Statistics. Physica-Verlag HD, 1992. http://dx.doi.org/10.1007/978-3-642-48678-4_6.

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Young, G. Alastair, and Thomas J. DiCiccio. "Computer-intensive conditional inference." In Contributions to Statistics. Springer Milan, 2010. http://dx.doi.org/10.1007/978-88-470-1386-5_11.

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Stephens, D. A., and A. F. M. Smith. "Bayesian Edge-Detection in Images via Changepoint Methods." In Computer Intensive Methods in Statistics. Physica-Verlag HD, 1993. http://dx.doi.org/10.1007/978-3-642-52468-4_1.

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Gruet, Marie-Anne, Sylvie Huet, and Emmanuel Jolivet. "Practical Use of Bootstrap in Regression." In Computer Intensive Methods in Statistics. Physica-Verlag HD, 1993. http://dx.doi.org/10.1007/978-3-642-52468-4_10.

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Besse, Ph, and A. de Falguerolles. "Application of Resampling Methods to the Choice of Dimension in Principal Component Analysis." In Computer Intensive Methods in Statistics. Physica-Verlag HD, 1993. http://dx.doi.org/10.1007/978-3-642-52468-4_11.

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Kleibergen, Frank, and Herman K. van Dijk. "Efficient Computer Generation of Matric-Variate t Drawings with an Application to Bayesian Estimation of Simple Market Models." In Computer Intensive Methods in Statistics. Physica-Verlag HD, 1993. http://dx.doi.org/10.1007/978-3-642-52468-4_2.

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Bauwens, L., and A. Rasquero. "Approximate HPD Regions for Testing Residual Autocorrelation Using Augmented Regressions." In Computer Intensive Methods in Statistics. Physica-Verlag HD, 1993. http://dx.doi.org/10.1007/978-3-642-52468-4_3.

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Wauters, Dirk, and Lea Vermeire. "Intensive Numerical and Symbolic Computing in Parametric Test Theory." In Computer Intensive Methods in Statistics. Physica-Verlag HD, 1993. http://dx.doi.org/10.1007/978-3-642-52468-4_4.

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Antoniadis, Anestis, Jacques Berruyer, and René Carmona. "Learning Data Analysis and Mathematical Statistics with a Macintosh." In Computer Intensive Methods in Statistics. Physica-Verlag HD, 1993. http://dx.doi.org/10.1007/978-3-642-52468-4_5.

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Roussignol, M., V. Jouanne, M. Menvielle, and P. Tarits. "Bayesian Electromagnetic Imaging." In Computer Intensive Methods in Statistics. Physica-Verlag HD, 1993. http://dx.doi.org/10.1007/978-3-642-52468-4_6.

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Conference papers on the topic "Computer-Intensive Statistics"

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Jones, Peter, Kay Lipson, and Brian Phillips. "A role for computer intensive methods in introducing statistical inference." In Proceedings of the First Scientific Meeting of the IASE. International Association for Statistical Education, 1993. http://dx.doi.org/10.52041/srap.93311.

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Introductory statistics courses have become increasingly prevalent in a wide variety of undergraduate and graduate programs over the past few years. This has resulted in the study of inferential statistics becoming the norm rather than exception. Whilst statistics was once a course chosen by the more mathematically able student, many current students of statistics have little mathematical aptitude or expertise (Tanis, 1992 for example). As a result, many introductory statistic courses have moved away from including much of the statistical theory that underpins inference to become basically tec

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Budgett, Stephanie, Maxine Pfannkuch, Matt Regan, and Chris Wild. "Dynamic visualizations for inference." In Technology in Statistics Education: Virtualities and Realities. International Association for Statistical Education, 2012. http://dx.doi.org/10.52041/srap.12103.

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Hypothesis testing reasoning is recognized as a difficult area for students. Changing to a new paradigm for learning inference through computer intensive methods rather than mathematical methods is a pathway that may be more successful. To explore ways to improve students’ inferential reasoning at the Year 13 (last year of school) and Stage One university levels, our research group developed new learning trajectories and dynamic visualizations for the randomization method. In this paper we report on the findings from a pilot study including student learning outcomes and on the modifications we

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"9 - Computer Intensive Statistical Inference." In 2005 Microwave Electronics: Measurements, Identification, Applications. IEEE, 2005. http://dx.doi.org/10.1109/ssp.2005.1628621.

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"25 - Special Session: Computer Intensive Statistical." In 2005 Microwave Electronics: Measurements, Identification, Applications. IEEE, 2005. http://dx.doi.org/10.1109/ssp.2005.1628789.

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Wang, G. Gary, and S. Shan. "Review of Metamodeling Techniques in Support of Engineering Design Optimization." In ASME 2006 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. ASMEDC, 2006. http://dx.doi.org/10.1115/detc2006-99412.

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Computation-intensive design problems are becoming increasingly common in manufacturing industries. The computation burden is often caused by expensive analysis and simulation processes in order to reach a comparable level of accuracy as physical testing data. To address such a challenge, approximation or metamodeling techniques are often used. Metamodeling techniques have been developed from many different disciplines including statistics, mathematics, computer science, and various engineering disciplines. These metamodels are initially developed as “surrogates” of the expensive simulation pr

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Luan, Lele, Nesar Ramachandra, Sandipp Krishnan Ravi, et al. "Scalable Probabilistic Modeling and Machine Learning With Dimensionality Reduction for Expensive High-Dimensional Problems." In ASME 2023 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2023. http://dx.doi.org/10.1115/detc2023-110704.

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Abstract Modern computational methods involving highly sophisticated mathematical formulations enable several tasks like modeling complex physical phenomena, predicting key properties, and optimizing design. The higher fidelity in these computer models makes it computationally intensive to query them hundreds of times for optimization. One usually relies on a simplified model, albeit at the cost of losing predictive accuracy and precision. Towards this, data-driven surrogate modeling methods have shown much promise in emulating the behavior of expensive computer models. However, a major bottle

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Fenga, Livio. "A Hybrid Computer-Intensive Approach Integrating Machine Learning and Statistical Methods for Fake News Detection." In ITISE 2024. MDPI, 2024. http://dx.doi.org/10.3390/engproc2024068047.

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Li, Shijia, Zhiyuan Wei, Shuguang Zhang, Zhaohui Cen, and Elias Tsoutsanis. "Polynomial Chaos Expansion-Based Uncertainty Model for Fast Assessment of Gas Turbine Aero-Engines Thrust Regulation: A Sparse Regression Approach." In ASME Turbo Expo 2024: Turbomachinery Technical Conference and Exposition. American Society of Mechanical Engineers, 2024. http://dx.doi.org/10.1115/gt2024-121246.

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Abstract Uncertainties in gas turbine aero-engines are unavoidable among which manufacturing tolerance is a typical manifestation. Uncertainties from manufacturing tolerance directly influence the thrust regulation performance, which may lead to the technical risks of newly produced aero-engines. Moreover, classic sample-based uncertainty quantification approaches are usually computationally intensive. In this paper, to consider the uncertainties in the control design phase in advance, a polynomial chaos expansion-based uncertainty model (PCEUM) using a sparse regression method is proposed to

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Drignei, Dorin, Zissimos P. Mourelatos, and Ramesh Rebba. "Parameter Screening in Dynamic Computer Model Calibration Using Global Sensitivities." In ASME 2010 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. ASMEDC, 2010. http://dx.doi.org/10.1115/detc2010-28343.

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Sensitivity analysis and computer model calibration are generally treated as two separate topics. In sensitivity analysis one quantifies the effect of each input factor on outputs, whereas in calibration one finds the values of input factors that provide the best match to a set of field data. In this paper we show a connection between these two seemingly separate concepts, and illustrate it with an automotive industry application involving a Road Load Acquisition Data (RLDA) computer model. We use global sensitivity analysis for computer models with transient responses to screen out inactive i

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Viana, Felipe A. C., Christian Gogu, and Raphael T. Haftka. "Making the Most Out of Surrogate Models: Tricks of the Trade." In ASME 2010 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. ASMEDC, 2010. http://dx.doi.org/10.1115/detc2010-28813.

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Design analysis and optimization based on high-fidelity computer experiments is commonly expensive. Surrogate modeling is often the tool of choice for reducing the computational burden. However, even after years of intensive research, surrogate modeling still involves a struggle to achieve maximum accuracy within limited resources. This work summarizes advanced and yet simple statistical tools that help. We focus on four techniques with increasing popularity in the design automation community: (i) screening and variable reduction in both the input and the output spaces, (ii) simultaneous use o

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