Concept
Semiparametric model
Publications associées (64)
Higher Order Asymptotics: Applications to Satellite Conjunction and Boundary Problems
Higher-order asymptotics provide accurate approximations for use in parametric statistical modelling. In this thesis, we investigate using higher-order approximations in two-specific settings, with a particular emphasis on the tangent exponential model. Th ...
EPFL2023Experimental data-driven model predictive control of a hospital HVAC system during regular use
Colin Neil Jones, Christophe Salzmann, Emilio Maddalena
Herein we report a multi-zone, heating, ventilation and air-conditioning (HVAC) control case study of an industrial plant responsible for cooling a hospital surgery center. The adopted approach to guaranteeing thermal comfort and reducing electrical energy ...
ELSEVIER SCIENCE SA2022Separating Algorithms From Questions and Causal Inference With Unmeasured Exposures: An Application to Birth Cohort Studies of Early Body Mass Index Rebound
Mats Julius Stensrud, Aaron Leor Sarvet
Observational studies reporting on adjusted associations between childhood body mass index (BMI; weight (kg)/height (m)(2)) rebound and subsequent cardiometabolic outcomes have often not paid explicit attention to causal inference, including definition of ...
2021Inference methods for the study of interacting biological oscillators in single-cells
Biological oscillators are pervasive in biology, covering all aspects of life from enzyme kinetics reactions to population dynamics. Although their behaviour has been intensively studied in the last decades, the recent advances of high-throughput experimen ...
EPFL2020Structural condition assessment of reinforced-concrete bridges based on acoustic emission and strain measurements
A reliable novel monitoring approach is developed to assess the structural condition of reinforced-concrete bridge elements. The approach is based on combining acoustic emission technique and strain gauge measurements, and it is illustrated by a case study ...
2020Unsupervised Robust Nonparametric Learning Of Hidden Community Properties
Martin Jaggi, Akhilesh Deepak Gotmare, Mikhail Langovoy
We consider learning of fundamental properties of communities in large noisy networks, in the prototypical situation where the nodes or users are split into two classes according to a binary property, e.g., according to their opinions or preferences on a t ...
2019Contributions to Likelihood-Based Modelling of Extreme Values
xtreme value analysis is concerned with the modelling of extreme events such as floods and heatwaves, which can have large impacts. Statistical modelling can be useful to better assess risks even if, due to scarcity of measurements, there is inherently ver ...
EPFL2019A practical method for seismic retrofit of tall buildings with supplemental damping
Current simplified design methods for buildings with supplemental damping devices are mainly based on single-degreefreedom (SDF) shear-models. Common errors of such methods are attributed to the linearization of nonlinear damping and stiffness, higher buil ...
CEI / SCE2019Validation of probabilistic classifiers
Michel Bierlaire, Timothy Michael Hillel
Non-parametric probabilistic classification models are increasingly being investigated as an
alternative to Discrete Choice Models (DCMs), e.g. for predicting mode choice. There exist many strategies within the literature for model selection between DCMs, ...
2018