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CSC@Lunch Seminar Series

We share a weekly seminar series with the Warwick Centre for Predictive Modelling (WCPM). Seminars are held from 1-2 pm on Mondays during the university term. Nominations for speakers are welcome. Please contact James Kermode or Peter Brommer with suggestions.

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Mon 3 Jun, '19
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Henrik Singmann (Warwick Psychology)
D2.02 Engineering

A Bayesian and Frequentist Multiverse Pipeline for Multinomial Processing Tree Models – Applications to Recognition Memory

Authors: Henrik Singmann (University of Warwick), Daniel W. Heck (Universität Mannheim), Marius Barth (Universität zu Köln), Julia Groß (Heinrich-Heine-Universität Düsseldorf), Beatrice G. Kuhlmann (Universität Mannheim)

Abstract: Even with a clear hypothesis or cognitive model in mind, most statistical analyses contain several more or less arbitrary choices. In the case of a model-based analysis, these choices can concern the statistical framework, the aggregation-level, and which parameter restrictions to introduce. Usually one path through this ‘garden of forking paths’ (Gelman & Loken, 2013) is chosen and reported. However, it is unclear how much each choice affects the reported results. The multiverse approach (Steegen, Tuerlinckx, Gelman, & Vanpaemel, 2016) offers a principled alternative in which results for all possible combinations of reasonable modeling choices are reported. We developed a software package for R that performs a model-based multiverse analysis for multinomial processing tree (MPT) models, MPTmultiverse. Our package estimates MPT models in a frequentist and Bayesian manner. In the frequentist case, it uses no pooling (with and without bootstrap) and complete pooling. In the Bayesian case, it uses no pooling, complete pooling, and three different variants of partial pooling. We applied our approach to a large confidence-rating recognition memory data corpus consisting of 12 studies with over 450 participants using a relatively unrestricted variant of the 2-high threshold model for confidence ratings (Bröder, Kellen, Schütz, & Rohrmeier, 2013). Our results show that even for some core parameters, the different analysis approaches reveal considerable variability in the parameter estimates across estimation methods. Our results suggest that researchers should adopt a multiverse approach when using cognitive models.

Mon 10 Jun, '19
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Sondipon Adhikari (Swansea)
PS0.17 Physical Sciences

Mechanics of geometrically disordered cellular materials

Metamaterials based on hexagonal periodic cells (honeycombs) have gained considerable attention in recent years. This can be an advanced material due to its capability of meeting high performance requirements in various critically desirable application-specific parameters. These structural assemblies not only make an efficient use of material but are also characterized by interesting dynamic and wave propagation properties. A semi-analytical formulation has been developed for wave propagation in irregular honeycombs. Spatial structural irregularity of hexagonal lattices has been considered. There are few scientific literatures available concerning analysis of wave propagation in regular honeycombs. However, due to inevitable uncertainties associated with manufacturing and service conditions, honeycomb lattices may not be always perfectly regular. The effect of spatially random structural irregularity in wave velocities of such irregular honeycombs will be discussed. Dynamic homogenisation of the metamaterials leads to some unusual properties such as negative elastic modulus at certain frequencies. New derivations are proposed to quantify and demystify such observations.

Mon 17 Jun, '19
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Joanna Leng (Leeds)
D2.02 Engineering

The Importance of Exploratory Visualization for Research

Mon 24 Jun, '19
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Francesca Baletto (KCL)
PS0.17 Physical Sciences

Architecture-sensitive catalytic activities made simple: a multi scale approach