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GSEVM v.2: MCMC software to analyze genetically structured environmental variance models

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GSEVM v.2: MCMC software to analyze genetically structured environmental variance models

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Ibáñez-Escriche, N.; Garcia, M.; Sorensen, D. (2010). GSEVM v.2: MCMC software to analyze genetically structured environmental variance models. Journal of Animal Breeding and Genetics. 127(3):249-251. https://doi.org/10.1111/j.1439-0388.2009.00846.x

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Title: GSEVM v.2: MCMC software to analyze genetically structured environmental variance models
Author: Ibáñez-Escriche, Noelia Garcia, M. Sorensen, D.
UPV Unit: Universitat Politècnica de València. Departamento de Ciencia Animal - Departament de Ciència Animal
Issued date:
Abstract:
[EN] This note provides a description of software that allows to fit Bayesian genetically structured variance models using Markov chain Monte Carlo (MCMC). The gsevm v.2 program was written in Fortran 90. The DOS and Unix ...[+]
Subjects: Bayesian analysis , Heterogeneous residual variance , MCMC software
Copyrigths: Cerrado
Source:
Journal of Animal Breeding and Genetics. (issn: 0931-2668 )
DOI: 10.1111/j.1439-0388.2009.00846.x
Publisher:
Blackwell Publishing
Publisher version: https://doi.org/10.1111/j.1439-0388.2009.00846.x
Thanks:
The authors are grateful to Rasmus Waagepetersen for computational and statistical input over the years.
Type: Artículo

References

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Ibáñez-Escriche, N., Sorensen, D., Waagepetersen, R., & Blasco, A. (2008). Selection for Environmental Variation: A Statistical Analysis and Power Calculations to Detect Response. Genetics, 180(4), 2209-2226. doi:10.1534/genetics.108.091678 [+]
Gutiérrez, J., Nieto, B., Piqueras, P., Ibáñez, N., & Salgado, C. (2006). Genetic parameters for canalisation analysis of litter size and litter weight traits at birth in mice. Genetics Selection Evolution, 38(5), 445. doi:10.1186/1297-9686-38-5-445

Henderson, C. R. (1976). A Simple Method for Computing the Inverse of a Numerator Relationship Matrix Used in Prediction of Breeding Values. Biometrics, 32(1), 69. doi:10.2307/2529339

Ibáñez-Escriche, N., Sorensen, D., Waagepetersen, R., & Blasco, A. (2008). Selection for Environmental Variation: A Statistical Analysis and Power Calculations to Detect Response. Genetics, 180(4), 2209-2226. doi:10.1534/genetics.108.091678

SanCristobal-Gaudy, M., Elsen, J.-M., Bodin, L., & Chevalet, C. (1998). Prediction of the response to a selection for canalisation of a continuous trait in animal breeding. Genetics Selection Evolution, 30(5), 423. doi:10.1186/1297-9686-30-5-423

Sorensen, D., & Gianola, D. (2002). Likelihood, Bayesian, and MCMC Methods in Quantitative Genetics. Statistics for Biology and Health. doi:10.1007/b98952

SORENSEN, D., & WAAGEPETERSEN, R. (2003). Normal linear models with genetically structured residual variance heterogeneity: a case study. Genetical Research, 82(3), 207-222. doi:10.1017/s0016672303006426

Spiegelhalter, D. J., Best, N. G., Carlin, B. P., & van der Linde, A. (2002). Bayesian measures of model complexity and fit. Journal of the Royal Statistical Society: Series B (Statistical Methodology), 64(4), 583-639. doi:10.1111/1467-9868.00353

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