Heteroscedastic ridge regression approaches for genome-wide prediction with a focus on computational efficiency and accurate effect estimation.
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The Current and Future Use of Ridge Regression for Prediction in Quantitative GeneticsPrediction accuracies for growth and wood attributes of interior spruce in space using genotyping-by-sequencing.Genome-wide prediction methods for detecting genetic effects of donor chromosome segments in introgression populations.A Ranking Approach to Genomic Selection.Genomic Prediction of Testcross Performance in Canola (Brassica napus).Genomic selection across multiple breeding cycles in applied bread wheat breedingGenomic selection of crossing partners on basis of the expected mean and variance of their derived lines.Genomic prediction applied to high-biomass sorghum for bioenergy production.
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P2860
Heteroscedastic ridge regression approaches for genome-wide prediction with a focus on computational efficiency and accurate effect estimation.
description
article científic
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article scientifique
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articolo scientifico
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artigo científico
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bilimsel makale
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scientific article published on 20 March 2014
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vedecký článok
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vetenskaplig artikel
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videnskabelig artikel
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vědecký článek
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name
Heteroscedastic ridge regressi ...... nd accurate effect estimation.
@en
Heteroscedastic ridge regressi ...... nd accurate effect estimation.
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type
label
Heteroscedastic ridge regressi ...... nd accurate effect estimation.
@en
Heteroscedastic ridge regressi ...... nd accurate effect estimation.
@nl
prefLabel
Heteroscedastic ridge regressi ...... nd accurate effect estimation.
@en
Heteroscedastic ridge regressi ...... nd accurate effect estimation.
@nl
P2860
P356
P1433
P1476
Heteroscedastic ridge regressi ...... nd accurate effect estimation.
@en
P2093
Matthias Frisch
Nina Hofheinz
P2860
P304
P356
10.1534/G3.113.010025
P577
2014-03-20T00:00:00Z