Hierarchical spatial modeling of additive and dominance genetic variance for large spatial trial datasets. - Wikidata - wikimedia - TriplyDB

Hierarchical spatial modeling of additive and dominance genetic variance for large spatial trial datasets.

Hierarchical spatial modeling of additive and dominance genetic variance for large spatial trial datasets.

http://www.wikidata.org/entity/Q37416095

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Hierarchical Spatial Process Models for Multiple Traits in Large Genetic Trials Multiple quantitative trait analysis using bayesian networks.Improving the performance of predictive process modeling for large datasets.Bayesian inference of genetic parameters based on conditional decompositions of multivariate normal distributions.Toward a diagnostic toolkit for linear models with Gaussian-process distributed random effects.Spatiotemporal prediction of infectious diseases using structured Gaussian processes with application to Crimean-Congo hemorrhagic fever Comparing and Blending Regional Climate Model Predictions for the American Southwest A novel individual-tree mixed model to account for competition and environmental heterogeneity: a Bayesian approach

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Hierarchical spatial modeling of additive and dominance genetic variance for large spatial trial datasets.

http://www.wikidata.org/entity/Q37416095

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 June 2009

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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

Hierarchical spatial modeling ...... large spatial trial datasets.

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Hierarchical spatial modeling ...... large spatial trial datasets.

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type

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Hierarchical spatial modeling ...... large spatial trial datasets.

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Hierarchical spatial modeling ...... large spatial trial datasets.

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Hierarchical spatial modeling ...... large spatial trial datasets.

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Hierarchical spatial modeling ...... large spatial trial datasets.

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J.1541-0420.2008.01115.X

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Hierarchical spatial modeling ...... large spatial trial datasets.

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Andrew O Finley

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Patrik Waldmann

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Sudipto Banerjee

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Tore Ericsson

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Computational Techniques for Spatial Logistic Regression with Large Datasets

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Pedigree analysis for quantitative traits: variance components without matrix inversion.

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Bayesian measures of model complexity and fit

ON STATIONARY PROCESSES IN THE PLANE

Bayesian estimation of a surface to account for a spatial trend using penalized splines in an individual-tree mixed model

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441-451

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scholarly article

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10.1111/J.1541-0420.2008.01115.X

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2

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65

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2009-06-01T00:00:00Z

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23226149

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18759829

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2775095

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