Learn R Programming

qtlmt (version 0.1-6)

sureEst: SURE model parameter estimation

Description

Estimate parameters in a SURE model.

Usage

sureEst(y, x, v, sigma, iter=10000, tol=1e-12)

Arguments

y

a n by p matrix, whose columns are dependent variables.

x

a n by m matrix, whose columns are predictor variables to select from.

v

a list; v[[j]] indicates which x's in the model for y[,j].

sigma

initial residual variance-covarance matrix (if given).

iter

maximum number of iterations in a numerical process to estimate model parameters.

tol

convergence tolerance.

Value

a list with the following components:

loglik

log-likelihood of the model

b

estimates of model coefficients

sigma

estimated residual variance-covariance

fitted.values

fitted mean values

Examples

Run this code
# NOT RUN {
data(etrait)
x<- as.matrix(mdat-1/2)
y<- as.matrix(traits)[,1:3]
v<- list(c(1,25,50),numeric(0),3)
# }
# NOT RUN {
o<- sureEst(y, x, v=v, iter=250, tol=1e-12)
# }

Run the code above in your browser using DataLab