نتائج البحث - "adaptive LASSO"

1

دورية أكاديمية

Combination of Ensembles of Regularized Regression Models with Resampling-Based Lasso Feature Selection in High Dimensional Data

المؤلفون: Abhijeet R Patil, Sangjin Kim

المصدر: Mathematics; Volume 8; Issue 1; Pages: 110

مصطلحات موضوعية: ensembles, feature selection, high-throughput, gene expression data, resampling, lasso, adaptive lasso, elastic net, SCAD, MCP

وصف الملف: application/pdf

العلاقة: Computational and Applied Mathematics; https://dx.doi.org/10.3390/math8010110Test

الإتاحة: https://doi.org/10.3390/math8010110Test

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2

دورية أكاديمية

Multiple Change-Points Estimation in Linear Regression Models via an Adaptive LASSO Expectile Loss Function

المؤلفون: Ciuperca, Gabriela, Dulac, Nicolas

المساهمون: Probabilités, statistique, physique mathématique (PSPM), Institut Camille Jordan (ICJ), École Centrale de Lyon (ECL), Université de Lyon-Université de Lyon-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université Jean Monnet - Saint-Étienne (UJM)-Centre National de la Recherche Scientifique (CNRS)-École Centrale de Lyon (ECL), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université Jean Monnet - Saint-Étienne (UJM)-Centre National de la Recherche Scientifique (CNRS), HD Technology SAS

المصدر: ISSN: 1559-8608 ; Journal of Statistical Theory and Practice ; https://hal.science/hal-04134097Test ; Journal of Statistical Theory and Practice, 2022, 16 (3), pp.38. ⟨10.1007/s42519-022-00265-9⟩.

مصطلحات موضوعية: Adaptive LASSO, Change-points, Expectile, Feature selection, Linear regression, [MATH]Mathematics [math]

العلاقة: hal-04134097; https://hal.science/hal-04134097Test

الإتاحة: https://doi.org/10.1007/s42519-022-00265-9Test
https://hal.science/hal-04134097Test

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3

Granger Causality Testing in High-Dimensional VARs: A Post-Double-Selection Procedure

المؤلفون: Stephan Smeekes, Alain Hecq, Luca Margaritella

المساهمون: QE Econometrics, RS: GSBE Theme Data-Driven Decision-Making, RS: GSBE Theme Learning and Work, RS: FSE DACS Mathematics Centre Maastricht

المصدر: Journal of Financial Econometrics, 21(3):nbab023, 915-958. Oxford University Press

مصطلحات موضوعية: FOS: Computer and information sciences, Economics and Econometrics, ADAPTIVE LASSO, Nuisance variable, Computer science, Econometrics (econ.EM), c12 - Hypothesis Testing: General, Feature selection, FREQUENCY, Least squares, Methodology (stat.ME), FOS: Economics and business, CONFIDENCE-INTERVALS, Set (abstract data type), Lasso (statistics), Granger causality, BOOTSTRAP, Econometrics, Statistics::Methodology, high-dimensional inference, post-double-selection, Statistics - Methodology, Selection (genetic algorithm), Economics - Econometrics, MODEL SELECTION, RISK, REGULARIZED ESTIMATION, vector autoregressive models, INFERENCE, SHRINKAGE, c32 - "Multiple or Simultaneous Equation Models: Time-Series Models, Dynamic Quantile Regressions, Dynamic Treatment Effect Models", Volatility (finance), Finance

الوصول الحر: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b5cc170b108e2bd84c294eeb69c6d3f2Test
https://doi.org/10.1093/jjfinec/nbab023Test

4

Two-step approach for assessing the health effects of environmental chemical mixtures: application to simulated datasets and real data from the Navajo Birth Cohort Study

المؤلفون: Ji-Hyun Lee, Johnnye Lewis, Laurie G. Hudson, Li Luo

المصدر: Environmental Health, Vol 18, Iss 1, Pp 1-16 (2019)
Environmental Health

مصطلحات موضوعية: Adult, Adolescent, Computer science, Health, Toxicology and Mutagenesis, Feature selection, computer.software_genre, Cohort Studies, Young Adult, 03 medical and health sciences, lcsh:RC963-969, Lasso (statistics), Pregnancy, Southwestern United States, Humans, Computer Simulation, Adaptive lasso, Chemical mixtures, 0303 health sciences, Models, Statistical, Random Forest, Research, Dimensionality reduction, lcsh:Public aspects of medicine, Public Health, Environmental and Occupational Health, 030311 toxicology, lcsh:RA1-1270, Environmental Exposure, Middle Aged, Regression, Random forest, Data set, Variable (computer science), Identification (information), Two-step approach, lcsh:Industrial medicine. Industrial hygiene, Environmental Pollutants, Female, Data mining, Environmental Health, computer

الوصول الحر: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8f70b1b01f83020432af63c40dc0486dTest
http://link.springer.com/article/10.1186/s12940-019-0482-6Test

5

Shrinkage priors for Bayesian penalized regression

المؤلفون: Van Erp, Sara, Oberski, Daniel L., Mulder, Joris, Leerstoel Klugkist, Methodology and statistics for the behavioural and social sciences

المساهمون: Leerstoel Klugkist, Methodology and statistics for the behavioural and social sciences

المصدر: Journal of Mathematical Psychology, 89, 31. Academic Press Inc.

مصطلحات موضوعية: shrinkage priors, ADAPTIVE LASSO, INFORMATION, Computer science, Overfitting, Social and Behavioral Sciences, computer.software_genre, 0302 clinical medicine, Sociology, Taverne, Physical Sciences and Mathematics, Psychology, Statistics::Methodology, General Psychology, Shrinkage, Computer Sciences, Applied Mathematics, 05 social sciences, Quantitative Psychology, Regression, FOS: Sociology, FOS: Psychology, REGULARIZATION, regression, HORSESHOE, Penalization, Statistics and Probability, Statistics::Theory, penalization, Bayesian probability, MODELS, Feature selection, Empirical Bayes, Machine learning, Bayesian, 050105 experimental psychology, Normal distribution, 03 medical and health sciences, Statistics::Machine Learning, Frequentist inference, Prior probability, 0501 psychology and cognitive sciences, empirical bayes, Shrinkage priors, business.industry, FREQUENTIST, Statistics::Computation, bayesian, Artificial intelligence, business, computer, 030217 neurology & neurosurgery, VARIABLE-SELECTION

وصف الملف: image/pdf

الوصول الحر: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4ed86355653a0fc0890764ac58840d89Test
https://doi.org/10.1016/j.jmp.2018.12.004Test

6

Testing the Lag Structure of Assets’ Realized Volatility Dynamics

المؤلفون: Lorenzo Camponovo, Constantin Roth, Francesco Audrino

المصدر: Quantitative Finance and Economics, Vol 1, Iss 4, Pp 363-387 (2017)

الوصول الحر: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::922bb6394245c6fa119d32e43a8767e1Test
https://doi.org/10.3934/qfe.2017.4.363Test

7

Combination of Ensembles of Regularized Regression Models with Resampling-Based Lasso Feature Selection in High Dimensional Data

المؤلفون: Sangjin Kim, Abhijeet R Patil

المصدر: Mathematics, Vol 8, Iss 1, p 110 (2020)
Mathematics
Volume 8
Issue 1

وصف الملف: application/pdf

الوصول الحر: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::042330fa9fae6f12e608391fd3fac702Test
https://www.mdpi.com/2227-7390/8/1/110Test

8

Oracle inequalities for high dimensional vector autoregressions

المؤلفون: Anders Bredahl Kock, Laurent Callot

المساهمون: Econometrics and Operations Research

المصدر: Callot, L & Kock, A B 2012 ' Oracle Inequalities for High Dimensional Vector Autoregressions ' Institut for Økonomi, Aarhus Universitet, Aarhus .
Kock, A & Callot, L A F 2015, ' Oracle Inequalities for High Dimensional Vector Autoregressions ', Journal of Econometrics, vol. 186, no. 2, pp. 325-344 . https://doi.org/10.1016/j.jeconom.2015.02.013Test
Kock, A B & Callot, L 2015, ' Oracle Inequalities for High-Dimensional Vector Autoregressions ', Journal of Econometrics, vol. 186, no. 2, pp. 325–344 . https://doi.org/10.1016/j.jeconom.2015.02.013Test
Journal of Econometrics, 186(2), 325-344. Elsevier BV