Robust discrete choice models with t-distributed kernel errors
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We analyze individual travel discomfort-time tradeoffs in Paris subway using stated choice experiments. The survey design allows to set up in a willingness-to-pay space to estimate the distributions of elasticities of values of travel time savings to crowd ...
Human mobility prediction is an important problem which has a large num- ber of applications, especially in context-aware services. This paper presents a study on location prediction using smartphone data, in which we address mod- eling and application asp ...
This paper proposes a distributionally robust approach to logistic regression. We use the Wasserstein distance to construct a ball in the space of probability distributions centered at the uniform distribution on the training samples. If the radius of this ...
Emissions of harmful substances into the atmosphere are a serious environmental concern. In order to understand and predict their effects, it is necessary to estimate the exact quantity and timing of the emissions, from sensor measurements taken at differe ...
Building simulation requires a large number of uncertain inputs and parameters. These include quantities that may be known with reasonable confidence, like the thermal properties of materials and building dimensions, but also inputs whose correct values ca ...
We present an operational estimation procedure for the estimation of route choice multivariate extreme value (MEV) models based on sampling of alternatives. The procedure builds on the state-of-the-art literature, and in particular on recent methodological ...
Commonly employed reconstruction algorithms in compressed sensing (CS) use the L-2 norm as the metric for the residual error. However, it is well-known that least squares (LS) based estimators are highly sensitive to outliers present in the measurement vec ...
Institute of Electrical and Electronics Engineers2013
This thesis tackles new challenges associated with the disaggregate modeling of the human behavior. Decision-aid tools help in making decisions, by providing quantitative insights on the decisions and associated consequences. They are useful in complex sit ...
We introduce a definition of the notion of compressibility for infinite deterministic and i.i.d. random sequences which is based on the asymptotic behavior of truncated subsequences. For this purpose, we use asymptotic results regarding the distribution of ...
In this paper, we investigate the construction of compromise estimators of location and scale, by averaging over several models selected among a specified large set of possible models. The weight given to each distribution is based on the profile likelihoo ...