Knowledge Center Catalog

High-dimensional sparse vine copula regression with application to genomic prediction (Record no. 68971)

MARC details
000 -LEADER
fixed length control field 02191nab a22003257a 4500
001 - CONTROL NUMBER
control field 68971
003 - CONTROL NUMBER IDENTIFIER
control field MX-TxCIM
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20250620160437.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 250611s2024 -us|||p|op||| 00| 0 eng d
022 ## - INTERNATIONAL STANDARD SERIAL NUMBER
International Standard Serial Number 0006-341X
022 ## - INTERNATIONAL STANDARD SERIAL NUMBER
International Standard Serial Number 1541-0420 (Online)
024 8# - OTHER STANDARD IDENTIFIER
Standard number or code https://doi.org/10.1093/biomtc/ujad042
040 ## - CATALOGING SOURCE
Original cataloging agency MX-TxCIM
041 ## - LANGUAGE CODE
Language code of text/sound track or separate title eng
100 1# - MAIN ENTRY--PERSONAL NAME
Personal name Sahin, Ö.
9 (RLIN) 39386
245 10 - TITLE STATEMENT
Title High-dimensional sparse vine copula regression with application to genomic prediction
260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT)
Place of publication, distribution, etc. United Kingdom :
Name of publisher, distributor, etc. Oxford University Press,
Date of publication, distribution, etc. 2024.
500 ## - GENERAL NOTE
General note Peer review
520 ## - SUMMARY, ETC.
Summary, etc. High-dimensional data sets are often available in genome-enabled predictions. Such data sets include nonlinear relationships with complex dependence structures. For such situations, vine copula-based (quantile) regression is an important tool. However, the current vine copula-based regression approaches do not scale up to high and ultra-high dimensions. To perform high-dimensional sparse vine copula-based regression, we propose 2 methods. First, we show their superiority regarding computational complexity over the existing methods. Second, we define relevant, irrelevant, and redundant explanatory variables for quantile regression. Then, we show our method’s power in selecting relevant variables and prediction accuracy in high-dimensional sparse data sets via simulation studies. Next, we apply the proposed methods to the high-dimensional real data, aiming at the genomic prediction of maize traits. Some data processing and feature extraction steps for the real data are further discussed. Finally, we show the advantage of our methods over linear models and quantile regression forests in simulation studies and real data applications.
546 ## - LANGUAGE NOTE
Language note Text in English
650 #7 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Genomics
9 (RLIN) 1132
Source of heading or term AGROVOC
650 #7 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Forecasting
Source of heading or term AGROVOC
9 (RLIN) 2701
650 #7 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Data
Source of heading or term AGROVOC
9 (RLIN) 9002
650 #7 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Regression analysis
Source of heading or term AGROVOC
9 (RLIN) 5834
650 #7 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Selection
Source of heading or term AGROVOC
9 (RLIN) 4749
650 #7 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Biometry
Source of heading or term AGROVOC
9 (RLIN) 9446
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Czado, C.
9 (RLIN) 39387
773 0# - HOST ITEM ENTRY
Place, publisher, and date of publication United Kingdom : Oxford University Press, 2024.
Related parts v. 80, no. 1, art. ujad042
Title Biometrics
International Standard Serial Number 0006-341X
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Source of classification or shelving scheme Dewey Decimal Classification
Koha item type Article
Suppress in OPAC No
Holdings
Date last seen Total Checkouts Price effective from Koha item type Lost status Source of classification or shelving scheme Damaged status Not for loan Collection code Withdrawn status Home library Current library Date acquired
06/11/2025   06/11/2025 Article Not Lost Dewey Decimal Classification     Reprints Collection   CIMMYT Knowledge Center: John Woolston Library CIMMYT Knowledge Center: John Woolston Library 06/11/2025

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