Faculty's seminar
You are here: Home
Thursday, September 20, 2018
Dean of the Faculty invites to
Faculty's Seminar, which will take place
on 27th of september at 12.15 in WS hall at Mathematical Institute. Lecture "The Confidence Trap:
dysfunctional dialogues about climate" will deliver
prof. Roger Cooke from TU Delft.
At 13.15 there will be the next lecture of prof. Rogera Cooke'a on "Abstract Vine Regression applied to the effects of breastfeeding duration on IQ"
Abstracts:
The Confidence Trap: dysfunctional dialogues about climate. Mutilation of facts, scriptural snake oil, gerrymandering the proof burden, bloated overconfidence and outright lies – these are among the miasmas fouling the public debate about climate change. The surprise is not that people try these stratagems, but that they are successful. A snarly cognitive illusion is preventing us from dealing rationally with climate uncertainties (a cognitive illusion is like an optical illusion involving the brain instead of the eyes). After a ‘syllabus of errors’, this talk focuses on better ways to capture and incorporate expert’s judgments on climate change. Developed in quantitative risk analysis, structured expert judgment has been used in a wide range of applications from nuclear safety, public health, investment banking to policy analysis and natural hazards. It is now poised to enter the climate debate in earnest. Can it help? Its time to find out.
Abstract Vine Regression applied to the effects of breastfeeding duration on IQ. If explanatory variables and a response variable of interest are simultaneously observed, then fitting a joint multivariate density to all variables would enable prediction via conditional distributions. Regular vines or vine copulas with arbitrary univariate margins provide a rich and flexible class of multivariate densities for Gaussian or non-Gaussian dependence structures. The density enables calculation of all regression functions for any subset of variables conditional on any disjoint set of variables, thereby avoiding issues of including/excluding covariates, interactions, higher order terms, multicollinearity, transformations, heteroscedasticity, bias, convergence and efficiency. Only the question of finding an adequate vine copula remains. Additionally, samples drawn from a vine distribution for which the regression functions are known enables studying the performance of various regression heuristics. This article illustrates vine regression with a data set from the National Longitudinal Study of Youth relating breastfeeding to IQ. The expected effects per week of additional breastfeeding on IQ depend strongly on IQ, the baseline level of breastfeeding, the duration of additional breastfeeding and on the values of other covariates. A child breastfed for 2 weeks can expect to increase his/her IQ by 1.4 to 2 points by adding 10 weeks of breastfeeding, depending on values of other covariates.
At 13.15 there will be the next lecture of prof. Rogera Cooke'a on "Abstract Vine Regression applied to the effects of breastfeeding duration on IQ"
Abstracts:
The Confidence Trap: dysfunctional dialogues about climate. Mutilation of facts, scriptural snake oil, gerrymandering the proof burden, bloated overconfidence and outright lies – these are among the miasmas fouling the public debate about climate change. The surprise is not that people try these stratagems, but that they are successful. A snarly cognitive illusion is preventing us from dealing rationally with climate uncertainties (a cognitive illusion is like an optical illusion involving the brain instead of the eyes). After a ‘syllabus of errors’, this talk focuses on better ways to capture and incorporate expert’s judgments on climate change. Developed in quantitative risk analysis, structured expert judgment has been used in a wide range of applications from nuclear safety, public health, investment banking to policy analysis and natural hazards. It is now poised to enter the climate debate in earnest. Can it help? Its time to find out.
Abstract Vine Regression applied to the effects of breastfeeding duration on IQ. If explanatory variables and a response variable of interest are simultaneously observed, then fitting a joint multivariate density to all variables would enable prediction via conditional distributions. Regular vines or vine copulas with arbitrary univariate margins provide a rich and flexible class of multivariate densities for Gaussian or non-Gaussian dependence structures. The density enables calculation of all regression functions for any subset of variables conditional on any disjoint set of variables, thereby avoiding issues of including/excluding covariates, interactions, higher order terms, multicollinearity, transformations, heteroscedasticity, bias, convergence and efficiency. Only the question of finding an adequate vine copula remains. Additionally, samples drawn from a vine distribution for which the regression functions are known enables studying the performance of various regression heuristics. This article illustrates vine regression with a data set from the National Longitudinal Study of Youth relating breastfeeding to IQ. The expected effects per week of additional breastfeeding on IQ depend strongly on IQ, the baseline level of breastfeeding, the duration of additional breastfeeding and on the values of other covariates. A child breastfed for 2 weeks can expect to increase his/her IQ by 1.4 to 2 points by adding 10 weeks of breastfeeding, depending on values of other covariates.
