Stephane Guerrier

Latest

• Equivalence Testing Under Privacy Constraints
• Inference for Large Scale Regression Models With Dependent Errors
• Accounting for Vibration Noise in Stochastic Measurement Errors of Inertial Sensors
• Wavelet Variance Based Robust Estimation of Composite Stochastic Models
• Accounting for Vibration Noise in Stochastic Measurement Errors
• Evidence of antagonistic predictive effects of miRNAs in breast cancer cohorts through data-driven networks
• Multi-Signal Approaches for Repeated Sampling Schemes in Inertial Sensor Calibration
• Non applicability of validated predictive models for intensive care admission and death of COVID-19 patients in a secondary care hospital in Belgium
• Granger-causal testing for irregularly sampled time series with application to nitrogen signalling in Arabidopsis
• Robust Two-Step Wavelet-Based Inference for Time Series Models
• Chameleon microRNAs in Breast Cancer: Their Elusive Role as Regulatory Factors in Cancer Progression
• Swag: A Wrapper Method for Sparse Learning
• Wavelet-Based Moment-Matching Techniques for Inertial Sensor Calibration
• Multivariate Signal Modeling With Applications to Inertial Sensor Calibration
• A Multisignal Wavelet Variance-Based Framework for Inertial Sensor Stochastic Error Modeling
• Applied Time Series Analysis With R
• Use of a New Online Calibration Platform With Applications to Inertial Sensors
• A Two-Step Computationally Efficient Procedure for IMU Classification and Calibration
• An Optimal Virtual Inertial Sensor Framework Using Wavelet Cross Covariance
• Improved Stochastic Modelling of Low-Cost GNSS Receivers Positioning Errors
• Is Nonmetastatic Cutaneous Melanoma Predictable Through Genomic Biomarkers?
• A Computationally Efficient Framework for Automatic Inertial Sensor Calibration
• A Computational Multivariate-Based Technique for Inertial Sensor Calibration
• An Automatic Calibration Approach for the Stochastic Parameters of Inertial Sensors
• A Study of the Allan Variance for Constant-Mean Nonstationary Processes
• An Overview of a New Sensor Calibration Platform
• Wavelet-Based Improvements for Inertial Sensor Error Modeling
• An R Package for Robust Time Series Analysis
• Fast and Robust Parametric Estimation for Time Series and Spatial Models
• On the Identifiability of Latent Models for Dependent Data
• The gmwm R Package: A Comprehensive Tool for Time Series Analysis From State-Space Models to Robustness
• Wavelet Variance for Random Fields: An M-Estimation Framework
• A Predictive Based Regression Algorithm for Gene Network Selection
• Discussion on Maximum Likelihood-Based Methods for Inertial Sensor Calibration
• Theoretical Limitations of Allan Variance-based Regression for Time Series Model Estimation
• Differentiating Inflammatory Bowel Diseases by Using Genomic Data: Dimension of the Problem and Network Organization
• Robust Inference for Time Series Models: A Wavelet-Based Framework
• A Paradigmatic Regression Algorithm for Gene Selection Problems
• An Inertial Sensor Calibration Platform to Estimate and Select Error Models
• A Computationally Efficient Platform for Inertial Sensor Calibration
• Automatic and Computationally Efficient Method for Model Selection in Inertial Sensor Calibration
• Automatic Identification and Calibration of Stochastic Parameters in Inertial Sensors
• Beyond Allan Variance-GMWM Framework for Sensor Calibration
• Estimation of time series models via robust wavelet variance
• Study of MEMS-Based Inertial Sensors Operating in Dynamic Conditions
• An Algorithm for Automatic Inertial Sensors Calibration