Zobrazeno 1 - 10
of 20
pro vyhledávání: '"Ezequiel Smucler"'
Publikováno v:
Journal of Statistical Software, Vol 92, Iss 1, Pp 1-23 (2020)
gdpc is an R package for the computation of the generalized dynamic principal components proposed in Peña and Yohai (2016). In this paper, we briefly introduce the problem of dynamical principal components, propose a solution based on a reconstructi
Externí odkaz:
https://doaj.org/article/5c3e4092ea5948e9b0cf6ea9cdb74f34
Publikováno v:
International Journal of Forecasting. 37:1498-1508
We present the sparse estimation of one-sided dynamic principal components (ODPCs) to forecast high-dimensional time series. The forecast can be made directly with the ODPCs or by using them as estimates of the factors in a generalized dynamic factor
Publikováno v:
Biometrika. 109:49-65
We study the selection of covariate adjustment sets for estimating the value of point exposure dynamic policies, also known as dynamic treatment regimes, assuming a non-parametric causal graphical model with hidden variables, in which at least one ad
Publikováno v:
Linear Algebra and its Applications. 610:785-803
We calculate bounds for orthant probabilities for the equicorrelated multivariate normal distribution and use these bounds to show the following: for degree k > 4 , the probability that a k-homogeneous polynomial in n variables attains a local constr
Autor:
Ezequiel Smucler, Andrea Rotnitzky
We study the selection of adjustment sets for estimating the interventional mean under an individualized treatment rule. We assume a non-parametric causal graphical model with, possibly, hidden variables and at least one adjustment set composed of ob
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::012631c0ecf0cf10b4cfc3781517f132
Autor:
Agustín Somacal, Yamila Barrera, Leonardo Boechi, Matthieu Jonckheere, Vincent Lefieux, Dominique Picard, Ezequiel Smucler
Publikováno v:
Physical review. E. 105(5-1)
SINDy is a method for learning system of differential equations from data by solving a sparse linear regression optimization problem [Brunton, Proctor, and Kutz, Proc. Natl. Acad. Sci. USA 113, 3932 (2016)PNASA60027-842410.1073/pnas.1517384113]. In t
Publikováno v:
Technometrics. 62:330-338
We propose an approach for fitting linear regression models that splits the set of covariates into groups. The optimal split of the variables into groups and the regularized estimation of the regression coefficients are performed by minimizing an obj
Publikováno v:
Journal of Multivariate Analysis. 171:339-349
We consider model-based sufficient dimension reduction for generalized linear models and prove the consistency and asymptotic normality of the prediction estimator studied empirically for the normal case by Adragni and Cook (2009) when a sample versi
Autor:
Matthieu Jonckheere, Yamila Barrera, Dominique Picard, Vincent Lefieux, Ezequiel Smucler, Agustín Somacal, Leonardo Boechi, Alfredo Umfurer
The Reseau de Transport d'Electricit\'e (RTE) is the French main electricity network operational manager and dedicates large number of resources and efforts towards understanding climate time series data. We discuss here the problem and the methodolo
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d7498e5e34f2c07736664d12ec7f4953
http://arxiv.org/abs/2012.07487
http://arxiv.org/abs/2012.07487
Publikováno v:
Ann. Appl. Stat. 13, no. 4 (2019), 2065-2090
In large-scale quantitative proteomic studies, scientists measure the abundance of thousands of proteins from the human proteome in search of novel biomarkers for a given disease. Penalized regression estimators can be used to identify potential biom
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1a4c624a451e79bff6c3614b99c7f673
https://projecteuclid.org/euclid.aoas/1574910036
https://projecteuclid.org/euclid.aoas/1574910036