56 citations · 364 across the 23 of their papers we have counts for
23 papers
Robust Bayesian causal estimation for causal inference in medical diagnosis
Tathagata Basu, Matthias C. M. Troffaes
Causal effect estimation is a critical task in statistical learning that aims to find the causal effect on subjects by identifying causal links between a number of predictor (or, e…
Regret-based budgeted decision rules under severe uncertainty
Nawapon Nakharutai, Sébastien Destercke, Matthias C. M. Troffaes
One way to make decisions under uncertainty is to select an optimal option from a possible range of options, by maximizing the expected utilities derived from a probability model.…
Data-driven Estimation of Under Frequency Load Shedding after Outages in Small Power Systems
Mohammad Rajabdorri, Lukas Sigrist, Enrique Lobato +2
This paper presents a data-driven methodology for estimating Under Frequency Load Shedding (UFLS) in small power systems. UFLS plays a vital role in maintaining system stability by…
Inclusion of Frequency Nadir constraint in the Unit Commitment Problem of Small Power Systems Using Machine Learning
Mohammad Rajabdorri, Behzad Kazemtabrizi, Matthias Troffaes +2
As the intention is to reduce the amount of thermal generation and to increase the share of clean energy, power systems are increasingly becoming susceptible to frequency instabili…
Iterative importance sampling with Markov chain Monte Carlo sampling in robust Bayesian analysis
Ivette Raices Cruz, Johan Lindström, Matthias C. M. Troffaes +1
Bayesian inference under a set of priors, called robust Bayesian analysis, allows for estimation of parameters within a model and quantification of epistemic uncertainty in quantit…
A robust Bayesian analysis of variable selection under prior ignorance
Tathagata Basu, Matthias C. M. Troffaes, Jochen Einbeck
We propose a cautious Bayesian variable selection routine by investigating the sensitivity of a hierarchical model, where the regression coefficients are specified by spike and sla…
A robust Bayesian bias-adjusted random effects model for consideration of uncertainty about bias terms in evidence synthesis
Ivette Raices Cruz, Matthias C. M. Troffaes, Johan Lindström +1
Meta-analysis is a statistical method used in evidence synthesis for combining, analyzing and summarizing studies that have the same target endpoint and aims to derive a pooled qua…
Improving and benchmarking of algorithms for -maximin, -maximax and interval dominance
Nawapon Nakharutai, Matthias C. M. Troffaes, Camila C. S. Caiado
-maximin, -maximax and inteval dominance are familiar decision criteria for making decisions under severe uncertainty, when probability distributions can only be partially id…
Robust decision analysis under severe uncertainty and ambiguous tradeoffs: an invasive species case study
Ullrika Sahlin, Matthias C. M. Troffaes, Lennart Edsman
Bayesian decision analysis is a useful method for risk management decisions, but is limited in its ability to consider severe uncertainty in knowledge, and value ambiguity in manag…
Improving and benchmarking of algorithms for decision making with lower previsions
Nawapon Nakharutai, Matthias C. M. Troffaes, Camila C. S. Caiado
Maximality, interval dominance, and E-admissibility are three well-known criteria for decision making under severe uncertainty using lower previsions. We present a new fast algorit…
Evaluating betting odds and free coupons using desirability
Nawapon Nakharutai, Camila C. S. Caiado, Matthias C. M. Troffaes
In the UK betting market, bookmakers often offer a free coupon to new customers. These free coupons allow the customer to place extra bets, at lower risk, in combination with the u…
Improved linear programming methods for checking avoiding sure loss
Nawapon Nakharutai, Matthias C. M. Troffaes, Camila C. S. Caiado
We review the simplex method and two interior-point methods (the affine scaling and the primal-dual) for solving linear programming problems for checking avoiding sure loss, and pr…
Imprecise Monte Carlo simulation and iterative importance sampling for the estimation of lower previsions
Matthias C. M. Troffaes
We develop a theoretical framework for studying numerical estimation of lower previsions, generally applicable to two-level Monte Carlo methods, importance sampling methods, and a…
A geometric and game-theoretic study of the conjunction of possibility measures
Enrique Miranda, Matthias C. M. Troffaes, Sebastien Destercke
In this paper, we study the conjunction of possibility measures when they are interpreted as coherent upper probabilities, that is, as upper bounds for some set of probability meas…
A robust Bayesian approach to modelling epistemic uncertainty in common-cause failure models
Matthias C. M. Troffaes, Gero Walter, Dana Kelly
In a standard Bayesian approach to the alpha-factor model for common-cause failure, a precise Dirichlet prior distribution models epistemic uncertainty in the alpha-factors. This D…
Identifying subtree perfectness in decision trees
Nathan Huntley, Matthias C. M. Troffaes
In decision problems, often, utilities and probabilities are hard to determine. In such cases, one can resort to so-called choice functions. They provide a means to determine which…
Finite approximations to coherent choice
Matthias C. M. Troffaes
This paper studies and bounds the effects of approximating loss functions and credal sets on choice functions, under very weak assumptions. In particular, the credal set is assumed…
Robust detection of exotic infectious diseases in animal herds: A comparative study of three decision methodologies under severe uncertainty
Matthias C. M. Troffaes, John Paul Gosling
When animals are transported and pass through customs, some of them may have dangerous infectious diseases. Typically, due to the cost of testing, not all animals are tested: a rea…
Subtree perfectness, backward induction, and normal-extensive form equivalence for single agent sequential decision making under arbitrary choice functions
Nathan Huntley, Matthias C. M. Troffaes
We revisit and reinterpret Selten's concept of subgame perfectness in the context of single agent normal form sequential decision making, which leads us to the concept of subtree p…
Normal form backward induction for decision trees with coherent lower previsions
Nathan Huntley, Matthias C. M. Troffaes
We examine normal form solutions of decision trees under typical choice functions induced by lower previsions. For large trees, finding such solutions is hard as very many strategi…
On the connection between probability boxes and possibility measures
Matthias C. M. Troffaes, Enrique Miranda, Sebastien Destercke
We explore the relationship between possibility measures (supremum preserving normed measures) and p-boxes (pairs of cumulative distribution functions) on totally preordered spaces…
Probability boxes on totally preordered spaces for multivariate modelling
Matthias C. M. Troffaes, Sebastien Destercke
A pair of lower and upper cumulative distribution functions, also called probability box or p-box, is among the most popular models used in imprecise probability theory. They arise…
n-Monotone exact functionals
Gert de Cooman, Matthias C. M. Troffaes, Enrique Miranda
We study n-monotone functionals, which constitute a generalisation of n-monotone set functions. We investigate their relation to the concepts of exactness and natural extension, wh…