MTGS.kmlasso: Genomic Selection using Kernelized Multivariate LASSO...
In MTGS: Genomic Selection using Multiple Traits
Description
Usage
Arguments
Value
References
Examples
Description
Calculates the Genomic Estimated Breeding Value based on KMLASSO method.
Usage
1
MTGS.kmlasso(X, Y)
Arguments
X
X is a design matrix of marker genotype of size n×p, where n are no of Individuals under study (i.e. genotype, lines) and p are no of markers.
Y
Y is matrix of individuals (n) with their phenotypic traits (q) of size n×q.
Value
$fit Lists various coeffecient assocaited to LASSO model fitting.
$Pred GEBV's for genotype/individuals under study.
References
Tibshirani, R. 1996. Regression shrinkage and selection via the lasso. J. R. Stat. Soc. Series B (Methodological). 267–288.
Searle, S.R., G. Casella and C.E. McCulloch. 1992. Variance Components. John Wiley, Hoboken.
Friedman, J., Hastie, T. and Tibshirani, R. (2008) Regularization Paths for Generalized Linear Models via Coordinate Descent, https://web.stanford.edu/~hastie/Papers/glmnet.pdf Journal of Statistical Software, Vol. 33(1), 1-22 Feb 2010 http://www.jstatsoft.org/v33/i01/.
Jerome Friedman, Trevor Hastie, Robert Tibshirani (2010). Regularization Paths for Generalized Linear Models via Coordinate Descent. Journal of Statistical Software, 33(1), 1-22. URL http://www.jstatsoft.org/v33/i01/.
Examples
1
2
3
4
5
6
library(MTGS)
data(brassica_data)
X<-brassica_data[,1:100]
Y<-brassica_data[,101:103]
#r<-0.25
MTGS.kmlasso(X,Y)
MTGS documentation built on Oct. 30, 2019, 11:12 a.m.
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Description Usage Arguments Value References Examples
Description
Calculates the Genomic Estimated Breeding Value based on KMLASSO method.
Usage
1 | MTGS.kmlasso(X, Y)
|
Arguments
X |
X is a design matrix of marker genotype of size n×p, where n are no of Individuals under study (i.e. genotype, lines) and p are no of markers. |
Y |
Y is matrix of individuals (n) with their phenotypic traits (q) of size n×q. |
Value
$fit Lists various coeffecient assocaited to LASSO model fitting.
$Pred GEBV's for genotype/individuals under study.
References
Tibshirani, R. 1996. Regression shrinkage and selection via the lasso. J. R. Stat. Soc. Series B (Methodological). 267–288.
Searle, S.R., G. Casella and C.E. McCulloch. 1992. Variance Components. John Wiley, Hoboken.
Friedman, J., Hastie, T. and Tibshirani, R. (2008) Regularization Paths for Generalized Linear Models via Coordinate Descent, https://web.stanford.edu/~hastie/Papers/glmnet.pdf Journal of Statistical Software, Vol. 33(1), 1-22 Feb 2010 http://www.jstatsoft.org/v33/i01/.
Jerome Friedman, Trevor Hastie, Robert Tibshirani (2010). Regularization Paths for Generalized Linear Models via Coordinate Descent. Journal of Statistical Software, 33(1), 1-22. URL http://www.jstatsoft.org/v33/i01/.
Examples
1 2 3 4 5 6 | library(MTGS)
data(brassica_data)
X<-brassica_data[,1:100]
Y<-brassica_data[,101:103]
#r<-0.25
MTGS.kmlasso(X,Y)
|
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