Results 11 to 20 of about 7,151,646 (328)

Extremile Regression [PDF]

Journal of the American Statistical Association, 2021
Regression extremiles define a least squares analogue of regression quantiles. They are determined by weighted expectations rather than tail probabilities. Of special interest is their intuitive meaning in terms of expected minima and maxima. Their use appears naturally in risk management where, in contrast to quantiles, they fulfill the coherency ...
Abdelaati Daouia, Irène Gijbels, Gilles Stupfler   +2 more
openaire   +5 more sources

Collaborative regression [PDF]

Biostatistics, 2014
13 pages, 4 ...
Gross, Samuel M., Tibshirani, Robert
openaire   +3 more sources

Wasserstein Regression

Journal of the American Statistical Association, 2021
The analysis of samples of random objects that do not lie in a vector space is gaining increasing attention in statistics. An important class of such object data is univariate probability measures defined on the real line. Adopting the Wasserstein metric, we develop a class of regression models for such data, where random distributions serve as ...
Yaqing Chen, Zhenhua Lin, Hans-Georg M uller   +2 more
openaire   +2 more sources

Extending a physics-based constitutive model using genetic programming

Applications in Engineering Science, 2022
In material science, models are derived to predict emergent material properties (e.g. elasticity, strength, conductivity) and their relations to processing conditions.
Gabriel Kronberger, Evgeniya Kabliman, Johannes Kronsteiner, Michael Kommenda   +3 more
doaj  

A Gaussian Mixture Model Clustering Ensemble Regressor for Semiconductor Manufacturing Final Test Yield Prediction

IEEE Access, 2021
In the semiconductor industry, many studies have been carried out for front-end related process improvement and yield prediction using machine learning techniques.
Dan Jiang, Weihua Lin, Nagarajan Raghavan   +2 more
doaj   +1 more source

Regression games [PDF]

, 2011
The solution of a TU cooperative game can be a distribution of the value of the grand coalition, i.e. it can be a distribution of the payo (utility) all the players together achieve.
A. Chevan, H. Moulin, H. P. Young, J. Stufken, L. S. Shapley, M. C. K. Powaga, M. Grabisch, M. Grabisch, Miklós Pintér, R. Babat, S. Lipovetsky, S. Lipovetsky, S. Lipovetsky, S. Lipovetsky, S. Lipovetsky, U. Grömping, U. Grömping, W. Conklin   +17 more
core   +1 more source

Application of symbolic regression for constitutive modeling of plastic deformation

Applications in Engineering Science, 2021
In numerical process simulations, in-depth knowledge about material behavior during processing in the form of trustworthy material models is crucial.
Evgeniya Kabliman, Ana Helena Kolody, Johannes Kronsteiner, Michael Kommenda, Gabriel Kronberger   +4 more
doaj  

Examining Spectral Reflectance Saturation in Landsat Imagery and Corresponding Solutions to Improve Forest Aboveground Biomass Estimation

Remote Sensing, 2016
The data saturation problem in Landsat imagery is well recognized and is regarded as an important factor resulting in inaccurate forest aboveground biomass (AGB) estimation.
Panpan Zhao, Dengsheng Lu, Guangxing Wang, Chuping Wu, Yujie Huang, Shuquan Yu   +5 more
doaj   +1 more source

Better subset regression [PDF]

, 2013
To find efficient screening methods for high dimensional linear regression models, this paper studies the relationship between model fitting and screening performance.
Xiong, Shifeng
core   +1 more source

Bayesian Linear Regression [PDF]

, 2009
The paper is concerned with Bayesian analysis under prior-data conflict, i.e. the situation when observed data are rather unexpected under the prior (and the sample size is not large enough to eliminate the influence of the prior).
Augustin, Thomas, Walter, Gero
core   +1 more source