A guide for kernel generalized regression methods for genomic-enabled prediction
Type:
Title:
A guide for kernel generalized regression methods for genomic-enabled prediction
Creator:
Montesinos-Lopez, A.;
Montesinos-Lopez, O.A.;
https://orcid.org/0000-0002-3973-6547
Scopus ID
Items in this Repository
View
Montesinos-Lopez, J.C.;
Flores-Cortes, C.A.;
Rosa, R. de la;
Crossa, J.
Montesinos-Lopez, O.A.;
Montesinos-Lopez, O.A.


View
Montesinos-Lopez, J.C.;
Flores-Cortes, C.A.;
Rosa, R. de la;
Crossa, J.

Year:
United Kin
Copyright:
CIMMYT manages Intellectual Assets as International Public Goods. The user is free to download, print, store and share this work. In case you want to translate or create any other derivative work and share or distribute such translation/derivative work, please contact CIMMYT-Knowledge-Center@cgiar.org indicating the work you want to use and the kind of use you intend; CIMMYT will contact you with the suitable license for that purpose
Journal:
Heredity
Journal volume:
In press
Place of Publication:
Springer Nature,
Publisher:
2021.
Citation:
A guide for kernel generalized regression methods for genomic-enabled prediction. United Kingdom :. In press DOI: 10.1038/s41437-021-00412-1 2021..