Robust discrete choice models with t-distributed kernel errors
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In the context of sales of new cars it is important to understand and model the consumers substitution patterns as well as their price elasticity towards different types of cars. To do so we develop (i) a multinomial logit model (MNL) and (ii) a cross-nest ...
We analyze individual travel discomfort-time tradeoffs in the 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 to crowd den ...
The joint bilateral filter is a variant of the standard bilateral filter, where the range kernel is evaluated using a guidance signal instead of the original signal. It has been successfully applied to various image processing problems, where it provides m ...
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In this paper we extend the Multiple Indicator Solution (MIS),used to correct for endogeneity, so that it can also be used when there are interactions between observed and unobserved factors in the specification of the utility function. We show the theoret ...
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 ...
The least-mean squares algorithm is non-robust against impulsive noise. Incorporating an error nonlinearity into the update equation is one useful way to mitigate the effects of impulsive noise. This work develops an adaptive structure that parametrically ...
Extreme events can be statistically characterised as excesses of a high threshold. Inference in this case has to account for dependence between excesses. The peaks over threshold approach suggests pre-processing the series by defining clusters of successiv ...
Recent interest in the topic of random scale heterogeneity in discrete choice data has led to the development of specialised tools such as the G-MNL model, as well as repeated claims that studies which fail to separate scale heterogeneity from heterogeneit ...
In this paper, we derive elementary M- and optimally robust asymptotic linear (AL)-estimates for the parameters of an Ornstein-Uhlenbeck process. Simulation and estimation of the process are already well-studied, see Iacus (Simulation and inference for sto ...