11 citations · 18 across the 11 of their papers we have counts for
11 papers
An accurate percentile method for parametric inference based on asymptotically biased estimators
Samuel Orso, Mucyo Karemera, Maria-Pia Victoria-Feser +1
Inference methods for computing confidence intervals in parametric settings usually rely on consistent estimators of the parameter of interest. However, it may be computationally a…
Accounting for Vibration Noise in Stochastic Measurement Errors
Lionel Voirol, Davide A. Cucci, Mucyo Karemera +3
The measurement of data over time and/or space is of utmost importance in a wide range of domains from engineering to physics. Devices that perform these measurements therefore nee…
Just Identified Indirect Inference Estimator: Accurate Inference through Bias Correction
Yuming Zhang, Yanyuan Ma, Samuel Orso +3
An important challenge in statistical analysis lies in controlling the estimation bias when handling the ever-increasing data size and model complexity of modern data settings. In…
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…
Matrix Dilogarithm as a -Symbol
Mucyo Karemera
We construct quantum invariants of 3-manifolds based on a matrix dilogarithm proposed by Kashaev. This matrix dilogarithm is an analogue of the…
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…
Wavelet-Based Moment-Matching Techniques for Inertial Sensor Calibration
Stéphane Guerrier, Juan Jurado, Mehran Khaghani +9
The task of inertial sensor calibration has required the development of various techniques to take into account the sources of measurement error coming from such devices. The calib…
Phase Transition Unbiased Estimation in High Dimensional Settings
Stéphane Guerrier, Mucyo Karemera, Samuel Orso +1
An important challenge in statistical analysis concerns the control of the finite sample bias of estimators. For example, the maximum likelihood estimator has a bias that can resul…
Multivariate Signal Modelling with Applications to Inertial Sensor Calibration
Haotian Xu, Stéphane Guerrier, Roberto Molinari +1
The common approach to inertial sensor calibration for navigation purposes has been to model the stochastic error signals of individual sensors independently, whether as components…
A simple recipe for making accurate parametric inference in finite sample
Stéphane Guerrier, Mucyo Karemera, Samuel Orso +1
Constructing tests or confidence regions that control over the error rates in the long-run is probably one of the most important problem in statistics. Yet, the theoretical justifi…
On the Properties of Simulation-based Estimators in High Dimensions
Stéphane Guerrier, Mucyo Karemera, Samuel Orso +1
Considering the increasing size of available data, the need for statistical methods that control the finite sample bias is growing. This is mainly due to the frequent settings wher…