MARC details
000 -LEADER |
fixed length control field |
02580nab a22003497a 4500 |
001 - CONTROL NUMBER |
control field |
60854 |
003 - CONTROL NUMBER IDENTIFIER |
control field |
MX-TxCIM |
005 - DATE AND TIME OF LATEST TRANSACTION |
control field |
20240919020951.0 |
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION |
fixed length control field |
190823s2019 gw |||p|op||| 00| 0 eng d |
022 ## - INTERNATIONAL STANDARD SERIAL NUMBER |
International Standard Serial Number |
0040-5752 |
022 ## - INTERNATIONAL STANDARD SERIAL NUMBER |
International Standard Serial Number |
1432-2242 (Online) |
024 8# - OTHER STANDARD IDENTIFIER |
Standard number or code |
https://doi.org/10.1007/s00122-019-03303-6 |
040 ## - CATALOGING SOURCE |
Original cataloging agency |
MX-TxCIM |
041 0# - LANGUAGE CODE |
Language code of text/sound track or separate title |
eng |
100 1# - MAIN ENTRY--PERSONAL NAME |
9 (RLIN) |
2702 |
Personal name |
Montesinos-Lopez, A. |
245 12 - TITLE STATEMENT |
Title |
A robust Bayesian genome-based median regression model |
260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT) |
Place of publication, distribution, etc. |
Berlin (Germany) : |
Name of publisher, distributor, etc. |
Springer, |
Date of publication, distribution, etc. |
2019. |
500 ## - GENERAL NOTE |
General note |
Peer review |
520 ## - SUMMARY, ETC. |
Summary, etc. |
Key message: Current genome-enabled prediction models assumed errors normally distributed, which are sensitive to outliers. We propose a model with errors assumed to follow a Laplace distribution to deal better with outliers. Abstract: Current genome-enabled prediction models use regressions that fit the expected value (mean) of a response variable with errors assumed normally distributed, which are often sensitive to outliers, either genetic or environmental. For this reason, we propose a robust Bayesian genome median regression (BGMR) model that fits regressions to the medians of a distribution, with errors assumed to follow a Laplace distribution to deal better with outliers. The BGMR model was evaluated under a Bayesian framework with Markov Chain Monte Carlo sampling using a location–scale mixture representation of the Laplace distribution. The BGMR was implemented with two simulated and two real genomic data sets, and we compared its prediction performance with that of a conventional genomic best linear unbiased prediction (GBLUP) model and the Laplace maximum a posteriori (LMAP) method. The prediction accuracies of BGMR were higher than those of the GBLUP and LMAP methods when there were outliers. The BGMR model could be useful to breeders who need to predict and select genotypes based on data with unknown outliers. |
546 ## - LANGUAGE NOTE |
Language note |
Text in English |
591 ## - CATALOGING NOTES |
Affiliation |
Montesinos-Lopez, O.A. : Not in IRS Staff list, no CIMMYT Affiliation |
650 #7 - SUBJECT ADDED ENTRY--TOPICAL TERM |
Topical term or geographic name as entry element |
Genomes |
Miscellaneous information |
AGROVOC |
Source of heading or term |
|
9 (RLIN) |
1131 |
650 #7 - SUBJECT ADDED ENTRY--TOPICAL TERM |
Source of heading or term |
AGROVOC |
9 (RLIN) |
5834 |
Topical term or geographic name as entry element |
Regression analysis |
650 #7 - SUBJECT ADDED ENTRY--TOPICAL TERM |
Source of heading or term |
AGROVOC |
9 (RLIN) |
4013 |
Topical term or geographic name as entry element |
Bayesian theory |
650 #7 - SUBJECT ADDED ENTRY--TOPICAL TERM |
Source of heading or term |
AGROVOC |
9 (RLIN) |
4859 |
Topical term or geographic name as entry element |
Models |
700 1# - ADDED ENTRY--PERSONAL NAME |
Field link and sequence number |
I1706800 |
9 (RLIN) |
2700 |
Personal name |
Montesinos-Lopez, O.A. |
Miscellaneous information |
Genetic Resources Program |
700 1# - ADDED ENTRY--PERSONAL NAME |
9 (RLIN) |
10315 |
Personal name |
Villa-Diharce, E.R. |
700 1# - ADDED ENTRY--PERSONAL NAME |
9 (RLIN) |
7797 |
Personal name |
Gianola, D. |
700 1# - ADDED ENTRY--PERSONAL NAME |
Personal name |
Crossa, J. |
Miscellaneous information |
Genetic Resources Program |
Field link and sequence number |
CCJL01 |
9 (RLIN) |
59 |
773 0# - HOST ITEM ENTRY |
Place, publisher, and date of publication |
Berlin (Germany) : Springer, 2019. |
Related parts |
v. 132, no. 5, p. 1587-1606 |
Title |
Theoretical and Applied Genetics |
Record control number |
u444762 |
International Standard Serial Number |
0040-5752 |
942 ## - ADDED ENTRY ELEMENTS (KOHA) |
Source of classification or shelving scheme |
Dewey Decimal Classification |
Koha item type |
Article |
Suppress in OPAC |
No |