Publications related to Accurate parametric inference for small samples

Distributionally Robust Logistic Regression

Daniel Kuhn, Soroosh Shafieezadeh Abadeh, Peyman Mohajerin Esfahani

This paper proposes a distributionally robust approach to logistic regression. We use the Wasserstein distance to construct a ball in the space of probability distributions centered at the uniform distribution on the training samples. If the radius of this ...

2015

Sparsity-Driven Statistical Inference for Inverse Problems

Ulugbek Kamilov

This thesis addresses statistical inference for the resolution of inverse problems. Our work is motivated by the recent trend whereby classical linear methods are being replaced by nonlinear alternatives that rely on the sparsity of naturally occurring sig ...

EPFL2015

A Geometric View on Constrained M-Estimators

Volkan Cevher, Yen-Huan Li, Ya-Ping Hsieh, Nissim Zerbib

We study the estimation error of constrained M-estimators, and derive explicit upper bounds on the expected estimation error determined by the Gaussian width of the constraint set. Both of the cases where the true parameter is on the boundary of the constr ...

2015

Stream temperature prediction in ungauged basins: review of recent approaches and description of a new physics-derived statistical model

Michael Lehning, Marc Parlange, Bettina Schaefli, Aurélien Gallice

The development of stream temperature regression models at regional scales has regained some popularity over the past years. These models are used to predict stream temperature in ungauged catchments to assess the impact of human activities or climate chan ...

European Geosciences Union2015

A new robust and efficient estimator for ill-conditioned linear inverse problems with outliers

Martin Vetterli, Ali Zoubir, Marta Martinez-Camara

Solving a linear inverse problem may include difficulties such as the presence of outliers and a mixing matrix with a large condition number. In such cases a regularized robust estimator is needed. We propose a new tau-type regularized robust estimator tha ...

2015

Sparsistency of $\ell_1$-Regularized $M$-Estimators

Volkan Cevher, Jonathan Mark Scarlett, Yen-Huan Li

We consider the model selection consistency or sparsistency of a broad set of

\ell_1

-regularized

M

-estimators for linear and non-linear statistical models in a unified fashion. For this purpose, we propose the local structured smoothness condition (LSS ...

2015

Accurate Directional Inference for Vector Parameters in Linear Exponential Families

Anthony Christopher Davison

We consider inference on a vector-valued parameter of interest in a linear exponential family, in the presence of a finite-dimensional nuisance parameter. Based on higher-order asymptotic theory for likelihood, we propose a directional test whose p-value i ...

American Statistical Association2014

Exploratory Analysis of Endogeneity in Discrete Choice Models

Michel Bierlaire, Anna Fernández Antolín, Amanda Blomberg Stathopoulos

A model is said to be affected by endogeneity when its deterministic part is correlated with the error term. This is an issue that affects both linear models such as regression and non-linear models like discrete choice models. It is a classical and well s ...

2014

Different parameters - same prediction. An analysis of learning curves

Using data from student use of educational technologies to evaluate and improve cognitive models of learners is now a common approach in EDM. Such naturally occurring data poses modeling challenges when non-random factors drive what data is collected. Prio ...

2014

Identification of airway bacterial colonization by an electronic nose in Chronic Obstructive Pulmonary Disease

Background: Airway bacterial colonization by potentially pathogenic microorganisms occurs in a proportion of patients with Chronic Obstructive Pulmonary Disease (COPD). It increases airway inflammation and influences outcomes negatively. Yet, its diagnosis ...

Elsevier2014

Accurate parametric inference for small samples

Graph Chatbot

Chat with Graph Search

Distributionally Robust Logistic Regression

Sparsity-Driven Statistical Inference for Inverse Problems

A Geometric View on Constrained M-Estimators

Stream temperature prediction in ungauged basins: review of recent approaches and description of a new physics-derived statistical model

A new robust and efficient estimator for ill-conditioned linear inverse problems with outliers

Sparsistency of $\ell_1$-Regularized $M$-Estimators

Accurate Directional Inference for Vector Parameters in Linear Exponential Families

Exploratory Analysis of Endogeneity in Discrete Choice Models

Different parameters - same prediction. An analysis of learning curves

Identification of airway bacterial colonization by an electronic nose in Chronic Obstructive Pulmonary Disease

A new robust and efficient estimator for ill-conditioned linear inverse problems with outliers

Exploratory Analysis of Endogeneity in Discrete Choice Models

Distributionally Robust Logistic Regression

Stream temperature prediction in ungauged basins: review of recent approaches and description of a new physics-derived statistical model

Sparsistency of $\ell_1$-Regularized $M$-Estimators

Accurate Directional Inference for Vector Parameters in Linear Exponential Families

Sparsity-Driven Statistical Inference for Inverse Problems

A Geometric View on Constrained M-Estimators

Different parameters - same prediction. An analysis of learning curves

Identification of airway bacterial colonization by an electronic nose in Chronic Obstructive Pulmonary Disease