Publication
Robust regression through robust covariances
Publications associées (74)
Stratégies de compromis pour l'estimation des paramètres de régression et pour la classification floue
Model specification is an integral part of any statistical inference problem. Several model selection techniques have been developed in order to determine which model is the best one among a list of possible candidates. Another way to deal with this questi ...
EPFL2011Multiple Kernel Learning: A Unifying Probabilistic Viewpoint
We present a probabilistic viewpoint to multiple kernel learning unifying well-known regularised risk approaches and recent advances in approximate Bayesian inference relaxations. The framework proposes a general objective function suitable for regression, ...
2011Effects of service loading on the behaviour of a suspension bridge
Ian Smith, Ngoc Thanh Trinh, Irwanda Laory
In order to achieve reliable information about deterioration, it is important to differentiate between changes in structural behaviour due to service loading (temperature, wind and traffic) and changes resulting from damage when interpreting measurement da ...
2011Performance of two model-free data interpretation methods for continuous monitoring of structures under environmental variations
Ian Smith, Ngoc Thanh Trinh, Irwanda Laory
Interpreting measurement data from continuous monitoring of civil structures for structural health monitoring (SHM) is a challenging task. This task is even more difficult when measurement data are influenced by environmental variations, such as temperatur ...
2011Robust Multivariate and Nonlinear Time Series Models
Time series modeling and analysis is central to most financial and econometric data modeling. With increased globalization in trade, commerce and finance, national variables like gross domestic productivity (GDP) and unemployment rate, market variables lik ...
EPFL2010Methodologies for model-free data interpretation of civil engineering structures
Structural health monitoring (SHM) has the potential to provide quantitative and reliable data on the real condition of structures, observe the evolution of their behaviour and detect degradation This paper presents two methodologies for model-free data in ...
Elsevier2010Robust inference for generalized linear models
Generalized Linear Models have become a commonly used tool of data analysis. Such models are used to fit regressions for univariate responses with normal, gamma, binomial or Poisson distribution. Maximum likelihood is generally applied as fitting method. I ...
EPFL2009Safe density ratio modeling
An important problem in logistic regression modeling is the existence of the maximum likelihood estimators. In particular, when the sample size is small, the maximum likelihood estimator of the regression parameters does not exist if the data are completel ...
2009Explanatory Variables for per Capita Stocks and Flows of Copper and Zinc
A number of potential explanatory variables for the stocks and flows of copper and zinc in contemporary technological societies are co-analyzed with the tools of exploratory data analysis. A one-year analysis (circa 1994) is performed for 50 countries that ...
Massachusetts Institute of Technology Press2008Discrete choice modelling of combined mode and departure time
Typical daily decision-making process of individuals regarding use of transport system involves mainly three types of decisions: mode choice, departure time choice and route choice. This paper focuses on the mode and departure time choice processes and stu ...
2008