Description Usage Arguments Details Value Author(s) References See Also Examples
This function returns a list with one element in it which is the estimate of the variance component in the Fay Herriot Model using residual maximum likelihood method. The estimates are obtained as a solution of equations known as REML equations. The solution is obtained numerically using Fisher-scoring algorithm. For more details please see the package vignette and the references. Note that our function does not accept any missing values.
1 | resimaxilikelihood(response, designmatrix, sampling.var,maxiter)
|
response |
a numeric vector. It represents the response or the observed value in the Fay Herriot Model |
designmatrix |
a numeric matrix. The first column is a column of ones(also called the intercept). The other columns consist of observations of each of the covariates or the explanatory variable in Fay Herriot Model. |
sampling.var |
a numeric vector consisting of the known sampling variances of each of the small area levels. |
maxiter |
maximum number of iterations of fisher scoring |
For more details see the package vignette
estimate |
estimate of the variance component |
Abhishek Nandy
On measuring the variability of small area estimators under a basic area level model. Datta, Rao, Smith. Biometrika(2005),92, 1,pp. 183-196 Large Sample Techniques for Statistics, Springer Texts in Statistics. Jiming Jiang. Chapters - 4,12 and 13. Small Area Estimation, JNK Rao,Wiley 2003 Variance Components, Wiley Series in Probability and Statistics,2006 Searle, Casella, Mc-Culloh
prasadraoest
maximlikelihood
fayherriot
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