varfh {saeMSPE} | R Documentation |
Estimates of the variance component using several methods for Fay Herriot model.
Description
This function returns the estimate of variance component with several existing method for Fay Herriot model. This function does not accept missing values.
Usage
varfh(Y, X, D, method)
varOBP(Y, X, D)
Arguments
Y |
(vector). It represents the response value for Fay Herriot model. |
X |
(matrix). It stands for the available auxiliary values. |
D |
(vector). It represents the knowing sampling variance for Fay Herriot model. |
method |
Variance component estimation method. See "Details". |
Details
Default value for method
is 1, It represents the moment estimator, Also called ANOVA estimator, The available variance component estimation method are list as follows:
method = 1
represents the moment (MOM) estimator, ;
method = 2
represents the restricted maximum likelihood (REML) estimator;
method = 3
represents the maximum likelihood (ML) estimator;
method = 4
represents the empirical bayesian (EB) estimator;
Value
This function returns a list with components:
bhat |
(vector) Estimates of the unknown regression coefficients. |
Ahat |
(numeric) Estimates of the variance component. |
Author(s)
Peiwen Xiao, Xiaohui Liu, Yuzi Liu, Jiming Jiang, and Shaochu Liu
References
J. Jiang. Linear and Generalized Linear Mixed Models and Their Applications. 2007.
Examples
X = matrix(runif(10 * 3), 10, 3)
X[,1] = rep(1, 10)
D = (1:10) / 10 + 0.5
Y = X %*% c(0.5,1,1.5) + rnorm(10, 0, sqrt(2)) + rnorm(10, 0, sqrt(D))
varOBP(Y, X, D)
varfh(Y, X, D, 1)