1. |
- Gerlee, Philip, 1980, et al.
(author)
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Scientific Models : Red Atoms, White Lies and Black Boxes in a Yellow Book
- 2016
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Book (other academic/artistic)abstract
- A zebrafish, the hull of a miniature ship, a mathematical equation and a food chain - what do these things have in common? They are examples of models used by scientists to isolate and study particular aspects of the world around us. This book begins by introducing the concept of a scientific model from an intuitive perspective, drawing parallels to mental models and artistic representations. It then recounts the history of modelling from the 16th century up until the present day. The iterative process of model building is described and discussed in the context of complex models with high predictive accuracy versus simpler models that provide more of a conceptual understanding. To illustrate the diversity of opinions within the scientific community, we also present the results of an interview study, in which ten scientists from different disciplines describe their views on modelling and how models feature in their work. Lastly, it includes a number of worked examples that span different modelling approaches and techniques. It provides a comprehensive introduction to scientific models and shows how models are constructed and used in modern science. It also addresses the approach to, and the culture surrounding modelling in different scientific disciplines. It serves as an inspiration for model building and also facilitates interdisciplinary collaborations by showing how models are used in different scientific fields. The book is aimed primarily at students in the sciences and engineering, as well as students at teacher training colleges but will also appeal to interested readers wanting to get an overview of scientific modelling in general and different modelling approaches in particular.
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2. |
- Gerlee, Philip, 1980, et al.
(author)
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Scientific Models
- 2016
-
Book (other academic/artistic)abstract
- A zebrafish, the hull of a miniature ship, a mathematical equation and a food chain - what do these things have in common? They are examples of models used by scientists to isolate and study particular aspects of the world around us. This book begins by introducing the concept of a scientific model from an intuitive perspective, drawing parallels to mental models and artistic representations. It then recounts the history of modelling from the 16th century up until the present day. The iterative process of model building is described and discussed in the context of complex models with high predictive accuracy versus simpler models that provide more of a conceptual understanding. To illustrate the diversity of opinions within the scientific community, we also present the results of an interview study, in which ten scientists from different disciplines describe their views on modelling and how models feature in their work. Lastly, it includes a number of worked examples that span different modelling approaches and techniques. It provides a comprehensive introduction to scientific models and shows how models are constructed and used in modern science. It also addresses the approach to, and the culture surrounding modelling in different scientific disciplines. It serves as an inspiration for model building and also facilitates interdisciplinary collaborations by showing how models are used in different scientific fields. The book is aimed primarily at students in the sciences and engineering, as well as students at teacher training colleges but will also appeal to interested readers wanting to get an overview of scientific modelling in general and different modelling approaches in particular.
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3. |
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4. |
- Baresel, Christian, et al.
(author)
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Uncertainty-Accounting Environmental Policy and Management of Water Systems
- 2007
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In: Environmental Science & Technology. - : American Chemical Society (ACS). - 0013-936X .- 1520-5851. ; 41:10, s. 3653–3659-
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Journal article (peer-reviewed)abstract
- Environmental policies for water quality and ecosystemmanagement do not commonly require explicit stochasticaccounts of uncertainty and risk associated with thequantification and prediction of waterborne pollutant loadsand abatement effects. In this study, we formulate andinvestigate a possible environmental policy that does requirean explicit stochastic uncertainty account. We compareboth the environmental and economic resource allocationperformance of such an uncertainty-accounting environmentalpolicy with that of deterministic, risk-prone and riskaverseenvironmental policies under a range of differenthypothetical, yet still possible, scenarios. The comparisonindicates that a stochastic uncertainty-accountingpolicy may perform better than deterministic policies overa range of different scenarios. Even in the absence ofreliable site-specific data, reported literature values appearto be useful for such a stochastic account of uncertainty.
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5. |
- Sabahno, Hamed, et al.
(author)
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Variable parameters memory-type control charts for simultaneous monitoring of the mean and variability of multivariate multiple linear regression profiles
- 2024
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In: Scientific Reports. - : Nature Publishing Group. - 2045-2322. ; 14:1
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Journal article (peer-reviewed)abstract
- Variable parameters (VP) schemes are the most effective adaptive schemes in increasing control charts' sensitivity to detect small to moderate shift sizes. In this paper, we develop four VP adaptive memory-type control charts to monitor multivariate multiple linear regression profiles. All the proposed control charts are single-chart (single-statistic) control charts, two use a Max operator and two use an SS (squared sum) operator to create the final statistic. Moreover, two of the charts monitor the regression parameters, and the other two monitor the residuals. After developing the VP control charts, we developed a computer algorithm with which the charts' time-to-signal and run-length-based performances can be measured. Then, we perform extensive numerical analysis and simulation studies to evaluate the charts’ performance and the result shows significant improvements by using the VP schemes. Finally, we use real data from the national quality register for stroke care in Sweden, Riksstroke, to illustrate how the proposed control charts can be implemented in practice.
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6. |
- Mejia, A. F., et al.
(author)
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A Bayesian General Linear Modeling Approach to Cortical Surface fMRI Data Analysis
- 2020
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In: Journal of the American Statistical Association. - : Informa UK Limited. - 0162-1459 .- 1537-274X.
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Journal article (peer-reviewed)abstract
- Cortical surface functional magnetic resonance imaging (cs-fMRI) has recently grown in popularity versus traditional volumetric fMRI. In addition to offering better whole-brain visualization, dimension reduction, removal of extraneous tissue types, and improved alignment of cortical areas across subjects, it is also more compatible with common assumptions of Bayesian spatial models. However, as no spatial Bayesian model has been proposed for cs-fMRI data, most analyses continue to employ the classical general linear model (GLM), a "massive univariate" approach. Here, we propose a spatial Bayesian GLM for cs-fMRI, which employs a class of sophisticated spatial processes to model latent activation fields. We make several advances compared with existing spatial Bayesian models for volumetric fMRI. First, we use integrated nested Laplacian approximations, a highly accurate and efficient Bayesian computation technique, rather than variational Bayes. To identify regions of activation, we utilize an excursions set method based on the joint posterior distribution of the latent fields, rather than the marginal distribution at each location. Finally, we propose the first multi-subject spatial Bayesian modeling approach, which addresses a major gap in the existing literature. The methods are very computationally advantageous and are validated through simulation studies and two task fMRI studies from the Human Connectome Project. for this article, including a standardized description of the materials available for reproducing the work, are available as an online supplement.
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7. |
- Sabahno, Hamed, et al.
(author)
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New statistical and machine learning based control charts with variable parameters for monitoring generalized linear model profiles
- 2023
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In: Computers & industrial engineering. - : Elsevier. - 0360-8352 .- 1879-0550. ; 184
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Journal article (peer-reviewed)abstract
- In this research, we develop three statistical based control charts: the Hotelling’s T2, MEWMA (multivariate exponentially weighted moving average), and LRT (likelihood ratio test) as well as three machine learning (ML) based control charts: the ANN (artificial neural network), SVR (support vector regression), and RFR (random forest regression), for monitoring generalized linear model (GLM) profiles. We train these ML models with two different training methods to get a linear (regression) output and then apply our classification technique to see if the process is in-control or out-of-control, at each sampling time. In addition to developing the FP (fixed parameters) schemes, for the first time in GLM profiles, we design an adaptive VP (variable parameters) scheme for each control chart as well to increase the charts’ sensitivity in detecting shifts. We develop some algorithms with which the values of the control chart parameters in both FP and VP schemes can be obtained. Then, we develop two algorithms to measure the charts’ performance in both FP and VP schemes, by using the run-length and time-to-signal based performance measures. This is also the first control chart-related research that develops an algorithm to compute the performance measures that applies to any VP adaptive control scheme. After designing the control charts as well as performance measures, we perform extensive simulation studies and evaluate and compare all our control charts under different shift sizes and scenarios, and in three different simulation environments. Finally, we present a numerical example regarding a drug dose-response study to show how the proposed control charts can be implemented in real practice.
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8. |
- Pavlenko, Tatjana
(author)
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Feature Informativeness, Curse-of-Dimensionality and Error Probability in Discriminant Analysis
- 2001
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Doctoral thesis (other academic/artistic)abstract
- This thesis is based on four papers on high-dimensional discriminant analysis. Throughout, the curse-of-dimensionality effect on the precision of the discrimination performance is emphasized. A growing dimension asymptotic approach is used for assessing this effect and the limiting error probability are taken as the performance criteria. A combined effect of a high dimensionality and feature informativeness on the discrimination performance is evaluated.
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9. |
- Casarino, V., et al.
(author)
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On the variation operator for the Ornstein-Uhlenbeck semigroup in dimension one
- 2024
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In: Annali Di Matematica Pura Ed Applicata. - 0373-3114 .- 1618-1891. ; 203:1, s. 205-219
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Journal article (peer-reviewed)abstract
- Consider the variation seminorm of the Ornstein-Uhlenbeck semigroup Ht in dimension one, taken with respect to t. We show that this seminorm defines an operator of weak type (1, 1) for the relevant Gaussian measure. The analogous Lp estimates for 1 < p < 8 were already known.
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10. |
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Modern Problems in Insurance Mathematics
- 2014
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Editorial collection (peer-reviewed)abstract
- The boook is a compilation of 21 of the papers presented at the International Cramér Symposium on Insurance Mathematics (ICSIM) held at Stockholm University 0n 11-14 June, 2013.
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