Concept

Deming regression

Publications associées (32)

Improving sample and feature selection with principal covariates regression

Michele Ceriotti, Edgar Albert Engel, Benjamin Aaron Helfrecht, Sergei Kliavinek

Selecting the most relevant features and samples out of a large set of candidates is a task that occurs very often in the context of automated data analysis, where it improves the computational performance and often the transferability of a model. Here we ...

IOP PUBLISHING LTD2021

Functional lagged regression with sparse noisy observations

Victor Panaretos, Tomas Rubin

A functional (lagged) time series regression model involves the regression of scalar response time series on a time series of regressors that consists of a sequence of random functions. In practice, the underlying regressor curve time series are not always ...

WILEY2020

Investigating Scrape-Off Layer transport in alternative divertor geometries on the TCV tokamak

Roberto Maurizio

Thermonuclear fusion is a potentially clean and limitless energy source that can substantially change the current global electricity generation mix, which is highly dependent on limited fossil fuels. This thesis contributes to the development of fusion en ...

EPFL2020

Automatic L2 Regularization for Multiple Generalized Additive Models

Yousra El Bachir

Multiple generalized additive models are a class of statistical regression models wherein parameters of probability distributions incorporate information through additive smooth functions of predictors. The functions are represented by basis function expan ...

EPFL2019

Methodology And Convergence Rates For Functional Time Series Regression

Victor Panaretos, Tung Huy Pham

The functional linear model extends the notion of linear regression to the case where the response and covariates are iid elements of an infinite-dimensional Hilbert space. The unknown to be estimated is a Hilbert-Schmidt operator, whose inverse is by defi ...

STATISTICA SINICA2018

Geomedicine: opportunities of using spatial information to move toward more precision in public health - spatial approaches and clusters: an introduction for clinicians

Stéphane Joost, Idris Guessous

In this presentation we introduce basic knowledge about the use of located health data to detect clusters of disease prevalence. Most often, geographic maps are produced to represent health data. Medical information is transmitted through thematic chorop ...

2017

Current challenge in landscape genomics: what about the environmental counterpart of high-throughput genomic data?

Stéphane Joost

Landscape genomics aims to identify genomic regions having adaptive significance by combining genomic and environmental data using regression methods. As regards its genetic component, next-generation high throughput sequencing technologies became availabl ...

2017

Structured Dimensionality Reduction for Additive Model Regression

Pascal Frossard, Alhussein Fawzi

Additive models are regression methods which model the response variable as the sum of univariate transfer functions of the input variables. Key benefits of additive models are their accuracy and interpretability on many real-world tasks. Additive models a ...

Institute of Electrical and Electronics Engineers2016

On the sensitivity of buildings to climate

Parag Rastogi

Building simulation requires a large number of uncertain inputs and parameters. These include quantities that may be known with reasonable confidence, like the thermal properties of materials and building dimensions, but also inputs whose correct values ca ...

EPFL2016

Prediction of long-term memory scores in MCI based on resting-state fMRI

Dimitri Nestor Alice Van De Ville, Stephan Morgenthaler, Thomas William Arthur Bolton, Maria Giulia Preti, Djalel Eddine Meskaldji

Resting-state functional MRI (rs-fMRI) opens a window on large-scale organization of brain function. However, establishing relationships between resting-state brain activity and cognitive or clinical scores is still a difficult task, in particular in terms ...

Elsevier Sci Ltd2016

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