Heteroskedasticity-consistent standard errors

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Statistique
Analyse des données
Régression (statistiques)

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Publications associées (30)

Statistical limits of high-dimensional inference problems

Clément Dominique Luneau

This thesis focuses on two kinds of statistical inference problems in signal processing and data science. The first problem is the estimation of a structured informative tensor from the observation of a noisy tensor in which it is buried. The structure com ...

EPFL2021

Context-Aware Learning for Generative Models

José del Rocio Millán Ruiz, Ricardo Andres Chavarriaga Lozano, Robert Leeb, Serafeim Perdikis

This work studies the class of algorithms for learning with side-information that emerges by extending generative models with embedded context-related variables. Using finite mixture models (FMMs) as the prototypical Bayesian network, we show that maximum- ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2021

Probabilistic and Bayesian methods for uncertainty quantification of deterministic and stochastic differential equations

Giacomo Garegnani

In this thesis we explore uncertainty quantification of forward and inverse problems involving differential equations. Differential equations are widely employed for modeling natural and social phenomena, with applications in engineering, chemistry, meteor ...

EPFL2021

Deep Learning with Convolutional Neural Network for Proportional Control of Finger Movements from surface EMG Recordings

Silvestro Micera, Vincent Alexandre Mendez, Leonardo Pollina, Fiorenzo Artoni

The control of robotic prosthetic hands (RPHs) for upper limb amputees is far from optimal. Simultaneous and proportional finger control of a RPH based on EMG signals is still challenging. Based on EMG and kinematics recordings of subjects following a pre- ...

IEEE2021

Age-Dependent Asymmetry of Wrist Position Sense Is Not Influenced by Stochastic Tactile Stimulation

Jamie Paik, Olivier Lambercy, Harshal Arun Sonar

Stochastic stimulation has been shown to improve movement, balance, the sense of touch, and may also improve position sense. This stimulation can be non-invasive and may be a simple technology to enhance proprioception. In this study, we investigated wheth ...

2020

Reaching mK-scale stability in CP-ɸOTDR over daily measurements

Luc Thévenaz, Tiago Filipe Pimentel Das Neves, Luis Costa

We propose several processing methods to mitigate the probability of large errors in Chirped-pulse ɸOTDR, improving performances for long-term measurements. For no perturbation applied, we reach a 2 mK error after a 24 h experiment. ...

2020

A Sensor Fusion Approach to the Estimation of Instantaneous Velocity Using Single Wearable Sensor During Sprint

Kamiar Aminian, Frédéric Meyer, Salil Apte, Farzin Dadashi, Vincent Gremeaux

Power-Force-Velocity profile obtained during a sprint test is crucial for designing personalized training and evaluating injury risks. Estimation of instantaneous velocity is requisite for developing these profiles and the predominant method for this estim ...

2020

R2D2: A Region-Based Recursive Doppler Dealiasing Algorithm for Operational Weather Radar

Alexis Berne, Marco Gabella, Monika Feldmann, Daniel Wolfensberger

Region-based Recursive Doppler Dealiasing (R2D2) is a novel dealiasing algorithm to unfold Doppler velocity fields obtained by operational radar measurements. It specializes in resolving issues when the magnitude of the gate-to-gate velocity shear approach ...

2020

Towards Reliable Evaluation of Algorithms for Road Network Reconstruction from Aerial Images

Pascal Fua, Mateusz Kozinski, Leonardo Citraro

Existing connectivity-oriented performance measures rank road delineation algorithms inconsistently, which makes it difficult to decide which one is best for a given application. We show that these inconsistencies stem from design flaws that make the metri ...

2020

Simultaneous autoregressive models for spatial extremes

Emeric Rolland Georges Thibaud

Motivated by the widespread use of large gridded data sets in the atmospheric sciences, we propose a new model for extremes of areal data that is inspired by the simultaneous autoregressive (SAR) model in classical spatial statistics. Our extreme SAR model ...

WILEY2020

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