Projects funded by the NCN

Information on the principal investigator and host institution

Information of the project and the call

Keywords

Equipment

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High dimensional model selection with SLOPE - theoretical properties and applications

2016/23/B/ST1/00454

Keywords:

linear models gaussian graphical models model selection prediction false discovery rate

Descriptors:

  • ST1_13: Probability and statistics
  • ST1_18: Control theory and optimisation

Panel:

ST1 - Mathematics: all areas of mathematics, pure and applied, as well as mathematical foundations of computer science, physics and statistics

Host institution :

Uniwersytet Wrocławski, Wydział Matematyki i Informatyki

woj. dolnośląskie

Other projects carried out by the institution 

Principal investigator (from the host institution):

dr hab. Małgorzata Bogdan 

Number of co-investigators in the project: 4

Call: OPUS 12 - announced on 2016-09-15

Amount awarded: 542 150 PLN

Project start date (Y-m-d): 2017-07-18

Project end date (Y-m-d): 2020-09-17

Project duration:: 38 months (the same as in the proposal)

Project status: Project settled

Project description

Download the project description in a pdf file

Note - project descriptions were prepared by the authors of the applications themselves and placed in the system in an unchanged form.

Equipment purchased [PL]

  1. Komputer stacjonarny o dużej szybkości, objętości RAM mocy obliczeniowej (5 000 PLN)
  2. Laptop (10 000 PLN)

Information in the final report

  • Publication in academic press/journals (11)
  • Articles in post-conference publications (1)
  • Book publications / chapters in book publications (1)
  1. Rank-based Lasso - efficient methods for high-dimensional robust model selection
    Authors:
    W. Rejchel, M. Bogdan
    Academic press:
    Journal of Machine Learning Research (rok: 2020, tom: 21, strony: 17168), Wydawca: Microtome Publishing
    Status:
    Published
    DOI:
    brak - link to the publication
  2. Sparse Portfolio Selection via the sorted L1 - Norm
    Authors:
    P. Kremer, S. Lee, M. Bogdan, S. Paterlini
    Academic press:
    Journal of Banking and Finance (rok: 2020, tom: 110, strony: 105687), Wydawca: Elsevier
    Status:
    Published
    DOI:
    10.1016/j.jbankfin.2019.105687 - link to the publication
  3. High-dimensional robust regression and outliers detection with SLOPE
    Authors:
    A. Virouleau, A. Guilloux, S. Gaiffas, M. Bogdan
    Academic press:
    Journal of Machine Learning Research , Wydawca: Microtome Publishing
    Status:
    Submitted
    DOI:
    brak - link to the publication
  4. Sparse Index Clones via the sorted L1 - Norm
    Authors:
    P.Kremer, D.Brzyski, M. Bogdan, S. Paterlini
    Academic press:
    Quantitative Finance , Wydawca: Taylor and Francis
    Status:
    Submitted
    DOI:
    brak - link to the publication
  5. Ghost QTL and Hotspots in Experimental Crosses - Novel Approach for Modeling Polygenic Effects
    Authors:
    J. Wallin, M. Bogdan, P. A. Szulc, R.W. Doerge, D.O. Siegmund
    Academic press:
    Genetics (rok: 2021, tom: brak, strony: brak, wczesna publikacja online), Wydawca: Genetics Society of America
    Status:
    Published
    DOI:
    10.1093/genetics/iyaa041 - link to the publication
  6. Varclust: clustering variables using dimensionality reduction
    Authors:
    P. Sobczyk, S. Wilczynski, M. Bogdan, P. Graczyk, J. Josse, F. Panloup, V. Seegers, M. Staniak.
    Academic press:
    Advances in Data Analysis and Classification , Wydawca: Springer
    Status:
    Submitted
    DOI:
    brak - link to the publication
  7. Selecting predictive biomarkers from genomic data
    Authors:
    F. Frommlet, P. Szulc, F. Koenig, M. Bogdan.
    Academic press:
    Econometrics and Statistics , Wydawca: Elsevier
    Status:
    Submitted
    DOI:
    brak - link to the publication
  8. On the asymptotic properties of SLOPE
    Authors:
    M.Kos and M. Bogdan
    Academic press:
    Sankhya Ser.A (rok: 2020, tom: 82, strony: 499-532), Wydawca: Springer
    Status:
    Published
    DOI:
    10.1007/s13171-020-00212-5 - link to the publication
  9. A power analysis for knockoffs with the lasso coefficient-difference statistic
    Authors:
    A. Weinstein, W. Su, M. Bogdan, R. Barber, E. J. Candes
    Academic press:
    Annals of Statistics , Wydawca: Institute of Mathematical Statistics
    Status:
    Submitted
    DOI:
    brak - link to the publication
  10. Adaptive Bayesian SLOPE -- High-dimensional Model Selection with Missing Values
    Authors:
    W. Jiang, M. Bogdan, J. Josse, B. Miasojedow, V. Rockova, Trauma Base Group
    Academic press:
    Journal of Computational Graphical Statistics , Wydawca: Taylor and Francis
    Status:
    Submitted
    DOI:
    brak - link to the publication
  11. On the sign recovery by LASSO, thresholded LASSO and thresholded Basis Pursuit Denoising
    Authors:
    P.J.C. Tardivel, M. Bogdan
    Academic press:
    Scandinavian Journal of Statistics , Wydawca: Wiley
    Status:
    Submitted
    DOI:
    brak - link to the publication
  1. The strong screening rule for slope.
    Authors:
    J. Larsson, M. Bogdan, J. Wallin
    Conference:
    Advances in Neural Information Processing Systems (NeurIPS 2020) (rok: 2020, ), Wydawca: Curran Associates, Inc
    Data:
    konferencja 6.12.2020-12.12.2020
    Status:
    Published
  1. Identifying important predictors in large data bases - multiple testing and model selection
    Authors:
    F.Frommlet, M.Bogdan
    Book:
    Handbook of Multiple Comparisons , Wydawca: Chapman & Hall/CRC
    Status:
    Accepted for publication

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