A Methodology for Constructing Subjective Probability Distributions with Data

Quigley, John M.; Walls, Lesley

doi:10.1007/978-3-319-65052-4_7

Cited by 2 publications

(3 citation statements)

References 27 publications

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“…We assume the correlation between two processes has been specified by subjective judgement but that the marginal Gamma distributions have been estimated with observed data, hence an empirical Bayes inference approach is adopted (e.g. following Quigley and Walls 19 ). We assume a pool of HPPs each with a pair of correlated observations.…”

Section: Methodsmentioning

confidence: 99%

“…The dependencies were elicited from suitably qualified engineers using a structured process based on the method described in Quigley and Walls. 19 This elicitation methodology maps the model parameters to the engineering expertise then uses relevant data (say from related past design elements and/or test) to quantify the dependency in view of the elicited judgements. The elicitation approach, grounded in a specifically designed defensible protocol, was resource intensive.…”

Section: Introductionmentioning

confidence: 99%

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Is eliciting dependency worth the effort? A study for the multivariate Poisson-Gamma probability model

Schwarzenegger

Quigley

Walls

2021

Proceedings of the Institution of Mechanical Engineers, Part O:

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We examine whether it is worthwhile eliciting subjective judgements to account for dependency in a multivariate Poisson-Gamma probability model. The challenge of estimating reliability during product design motivated the choice of model class. For the multivariate Poisson-Gamma model we adopt an empirical Bayes methodology to present an estimator with improved accuracy. A simulation study investigates the estimation error of this estimator for different degrees of dependency and examines the impact of dependency being mis-specified when assessed by subjective judgement. Our theoretical and simulation findings give analysts insights about the value of eliciting dependency.

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Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Is eliciting dependency worth the effort? A study for the multivariate Poisson-Gamma probability model

Schwarzenegger

Quigley

Walls

2021

Proceedings of the Institution of Mechanical Engineers, Part O:

Self Cite

View full text Add to dashboard Cite

show abstract

“…We propose a six step approach adapted from the CISSE process, see [29], for constructing empirical prior distributions to support Bayesian analysis, which considers the following five steps; Characterize, Identify, Sentence, Select, and Estimate. As described in the following for the third step we have placed particular focus on homogenizing the data rather than sentencing the data and we have decomposed the fifth step to consider prediction and updating.…”

Section: Process For Constructing Marked Point Process Decision Supportmentioning

confidence: 99%

Design as a Marked Point Process

Quigley

Vasantha

Corney³

et al. 2021

Journal of Mechanical Design

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Although AI systems which support composition using predictive text are well established there are no analogous technologies for mechanical design. Motivated by the vision of a predictive system that interactively suggests features to designer, this paper describes the theory, implementation and assessment of an intelligent system that learns from a family of previous designs and generates inferences using a form of spatial statistics. The formalism presented, models 3D design activity as a ‘Marked Point Process’ that enables the probability of specific features being added at a particular locations to be calculated. Because the resulting probabilities are updated every time a new feature is added the predictions will become more accurate as a design develops. This approach allows the cursor position on a CAD model to implicitly define a spatial focus for every query made to the statistical model. The authors describe the mathematics underlying a statistical model that amalgamates the frequency of occurrence of the features in the existing designs of a product family. Having established the theoretical foundations of the work, a generic six step implementation process is described. This process is then illustrated for circular hole features using a statistical model generated from a dataset of hydraulic valves. The paper describes how the positions of each design's extracted hole features can be homogenized through rotation and scaling. Results suggest that within generic part families (i.e. designs with common structure) a marked point process can be effective at predicting incremental steps in the development of new designs.

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A Methodology for Constructing Subjective Probability Distributions with Data

Cited by 2 publications

References 27 publications

Is eliciting dependency worth the effort? A study for the multivariate Poisson-Gamma probability model

Is eliciting dependency worth the effort? A study for the multivariate Poisson-Gamma probability model

Design as a Marked Point Process

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