2 citations · 6 across the 7 of their papers we have counts for
11 papers
Scale-wise Variance Minimization for Optimal Virtual Signals: An Approach for Redundant Gyroscopes
Yuming Zhang, Davide A. Cucci, Roberto Molinari +1
The increased use of low-cost gyroscopes within inertial sensors for navigation purposes, among others, has brought to the development of a considerable amount of research in impro…
Multi-Signal Approaches for Repeated Sampling Schemes in Inertial Sensor Calibration
Gaetan Bakalli, Davide A. Cucci, Ahmed Radi +4
Inertial sensor calibration plays a progressively important role in many areas of research among which navigation engineering. By performing this task accurately, it is possible to…
Prevalence Estimation from Random Samples and Census Data with Participation Bias
Stéphane Guerrier, Christoph Kuzmics, Maria-Pia Victoria-Feser
Countries officially record the number of COVID-19 cases based on medical tests of a subset of the population with unknown participation bias. For prevalence estimation, the offici…
A General Approach for Simulation-based Bias Correction in High Dimensional Settings
Stéphane Guerrier, Mucyo Karemera, Samuel Orso +2
An important challenge in statistical analysis lies in controlling the bias of estimators due to the ever-increasing data size and model complexity. Approximate numerical methods a…
Asymptotically Optimal Bias Reduction for Parametric Models
Stéphane Guerrier, Mucyo Karemera, Samuel Orso +1
An important challenge in statistical analysis concerns the control of the finite sample bias of estimators. This problem is magnified in high-dimensional settings where the number…
Robust Two-Step Wavelet-Based Inference for Time Series Models
Stéphane Guerrier, Roberto Molinari, Maria-Pia Victoria-Feser +1
Complex time series models such as (the sum of) ARMA models with additional noise, random walks, rounding errors and/or drifts are increasingly used for data analysis in fie…