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

Journal of Animal Breeding and Genetics

Volumn 127, Issue 3, 2010, Pages 249-251

  Ibanez Escriche N ^a   Garcia, M ^b   Sorensen, D ^c  

^a IRTA   (Spain)

^b CEMAGREF   (France)

^c DANISH INSTITUTE OF AGRICULTURAL SCIENCES   (Denmark)

Author keywords

Bayesian analysis; Heterogeneous residual variance; MCMC software

Indexed keywords

ALGORITHM; ANALYSIS OF VARIANCE; ARTICLE; BAYES THEOREM; COMPUTER PROGRAM; MONTE CARLO METHOD; PROBABILITY; STATISTICAL MODEL;

ALGORITHMS; ANALYSIS OF VARIANCE; BAYES THEOREM; LINEAR MODELS; MARKOV CHAINS; MONTE CARLO METHOD; SOFTWARE;

EID: 77954062035     PISSN: 09312668     EISSN: 14390388     Source Type: Journal    
DOI: 10.1111/j.1439-0388.2009.00846.x     Document Type: Article

References (10)

1. Gutiérrez JP, Nieto B, Piqueras P, Ibanez N, Salgado C. Genetic parameters for canalisation analysis of litter size and litter weight traits at birth in mice. Genet. Sel. Evol. 2006, 38:445-462.
2. Henderson CR. A simple method for the inverse of a numerator relationship matrix used in prediction of breeding values. Biometrics 1976, 32:69-83.
3. Ibáñez-Escriche N, Varona L, Sorensen D, Noguera JL. A study of heterogeneity of environmental variance for slaughter weight in pigs. Animal 2007, 2:2209-2226.
4. Ibáñez-Escriche N, Moreno A, Nieto B, Piqueras P, Salgado C, Gutierrez JP. Genetic parameters related to environmental variability of weight traits in a selection experiment for weight gain in mice; signs of correlated canalized response. Genet. Sel. Evol. 2008, 40:279-293.
5. Ibáñez-Escriche N, Sorensen D, Waagepetersen R, Blasco A. Selection for environmental variation: a statistical analysis and power calculations to detect response. Genetics 2009, 180:2209-2226.
6. SanCristobal-Gaudy M, Elsen JM, Bodin L, Chevalet C. Prediction of the response to a selection for canalisation of a continuous trait in animal breeding. Genet. Sel. Evol. 1998, 30:423-451.
7. Sorensen D, Gianola D. Likelihood, Bayesian and Markov chain Monte Carlo methods in quantitative genetics 2002, Springer-Verlag, New York
8. Sorensen D, Waagepetersen R. Normal linear models with genetically structured variance heterogeneity: a case of study. Genet. Res. 2003, 82:207-222.
9. Spiegelhalter DJ, Best NG, Carlin BP, van der Linde A. Bayesian measures of model complexity and fit (with discussion). J. R. Stat. Soc., Ser. B 2002, 64:583-639.
10. Waagepetersen R, Ibáñez-Escriche N, Sorensen D. A comparison of strategies for Markov Chain Monte Carlo computation in quantitative genetics. Genet. Sel. Evol. 2008, 40:161-176.