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Smallest covering regions and highest density regions for discrete distributions
This paper examines the problem of computing a canonical smallest covering region for an arbitrary discrete probability distribution. This...
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Correction for Optimisation Bias in Structured Sparse High-Dimensional Variable Selection
In sparse high-dimensional data, the selection of a model can lead to an overestimation of the number of nonzero variables. Indeed, the use of an...
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Asset and Liability Risk Management in Financial Markets
Most financial organisations depend on their ability to match the assets and liabilities they hold. This managerial challenge has been traditionally...
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Information criteria bias correction for group selection
The main contribution of this paper lies in the extension towards group lasso of a Mallows’ Cp-like information criterion used in finetuning the...
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A Model-Based Approach to Assess Epidemic Risk
We study how international flights can facilitate the spread of an epidemic to a worldwide scale. We combine an infrastructure network of flight...
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Constrained optimization for addressing spatial heterogeneity in principal component analysis: an application to composite indicators
Principal component analysis, in its standard version, might not be appropriate for the analysis of spatial data. Particularly, the presence of...
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Semi-automated simultaneous predictor selection for regression-SARIMA models
Deciding which predictors to use plays an integral role in deriving statistical models in a wide range of applications. Motivated by the challenges...
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Co-clustering contaminated data: a robust model-based approach
The exploration and analysis of large high-dimensional data sets calls for well-thought techniques to extract the salient information from the data,...
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Reliability
This chapter introduces key concepts for quantification of system reliability. In addition, basics of statistical inference for reliability data are...
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Design of experiments and machine learning with application to industrial experiments
In the context of product innovation, there is an emerging trend to use Machine Learning (ML) models with the support of Design Of Experiments (DOE)....
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Exploring Proportions
We now turn to the study of proportions in the lengths of pieces of music, starting with some background on proportions in the arts in general...
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A fingerprint of a heterogeneous data set
In this paper, we describe the fingerprint method, a technique to classify bags of mixed-type measurements. The method was designed to solve a...
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Bayesian Computation with Intractable Likelihoods
This chapter surveys computational methods for posterior inference with intractable likelihoods, that is where the likelihood function is unavailable...
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Using a Spatial Farm Microsimulation Model for Australia to Estimate the Impact of an External Shock on Farmer Incomes
A greater uncertainty in climate conditions in Australia and external price shocks in commodity prices has posed a real question for communities on...
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A Note on Artificial Intelligence and Statistics
Now that data science receives a lot of attention, the three disciplines of data analysis, databases, and sciences are discussed with respect to the...
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Statistical Theory of Shape Under Elliptical Models via Polar Decompositions
A new model of statistical shape theory under elliptical models is proposed by using the polar decomposition. This work completes the group of SVD...
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Estimation of relative risk for events on a linear network
Motivated by the study of traffic accidents on a road network, we discuss the estimation of the relative risk, the ratio of rates of occurrence of...
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Splitting for Multi-objective Optimization
We introduce a new multi-objective optimization (MOO) methodology based the splitting technique for rare-event simulation. The method generalizes the...
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Bayesian computation: a summary of the current state, and samples backwards and forwards
Recent decades have seen enormous improvements in computational inference for statistical models; there have been competitive continual enhancements...
