infonet-economy

This research presents methods for detecting and isolating faults in multiple MEMS-IMU configurations. First, geometric configurations with n sensor triads are investigated. It is proofed that the relative orientation between sensor triads is irrelevant to system optimality in the absence of failures. Then, the impact of sensor failure or decreased performance is investigated. Three...

In this paper, we propose a new criterion for selection between nested models. We suppose that the correct model is one (or near one) of the available models and construct a criterion which is based on the Bregman divergence between the out-of-sample prediction of the smaller model and the in-sample prediction of the larger model. This criterion, the prediction divergence criterion (...

Filtering methods are powerful tools to estimate the hidden state of a statespace model from observations available in real time. However, they are known to be highly sensitive to the presence of small misspecifications of the underlying model and to outliers in the observation process. In this paper, we show that the methodology of robust statistics can be adapted to sequential...

Large datasets are more and more common in many research fields. In particular, in the linear regression context, it is often the case that a huge number of potential covariates are available to explain a response variable, and the first step of a reasonable statistical analysis is to reduce the number of covariates. This can be done in a forward selection procedure that includes the...

Stochastic modeling is a challenging task for low-cost sensors which errors can have complex spectral structures. This makes the tuning process of the INS/GNSS Kalman filter often sensitive and diffcult. For example, first-order Gauss-Markov processes are very often used in inertial sensor models. But the estimation of their parameters is a non-trivial task if the error structure is...

In this thesis, we develop models to analyze zero-inflated truncated heavy-tailed dependent data to fit radio audience data in Switzerland. These models are able to explain, by means of covariates, both the probability of observing a positive outcome and the mean of the positive outcomes, which respectively correspond to the audience indicators of reach and of time spent listening....