FHme | R Documentation |
This function gives the EBLUP estimator based on Fay-Herriot model with measurement error.
FHme( formula, vardir, var.x, type.x = "witherror", MAXITER = 1000, PRECISION = 1e-04, data )
formula |
an object of class |
vardir |
vector containing the |
var.x |
vector containing mean squared error of |
type.x |
type of auxiliary variable used in the model. Either source measured with |
MAXITER |
maximum number of iterations allowed. Default value is |
PRECISION |
convergence tolerance limit. Default value is |
data |
optional data frame containing the variables named in formula, vardir, and var.x. |
A formula has an implied intercept term. To remove this use either y ~ x - 1 or y ~ 0 + x. See formula
for more details of allowed formulae.
The function returns a list with the following objects:
eblup
vector with the values of the estimators for the domains.
fit
a list containing the following objects:
method
: type of fitting method.
convergence
: a logical value of convergence when calculating estimated beta and estimated random effects.
iterations
: number of iterations when calculating estimated beta and estimated random effects.
estcoef
: a data frame with the estimated model coefficient (beta
) in the first column, their standard error (std.error
) in the second column, the t-statistics (t.statistics
) in the third column, and the p-values of the significance of each coefficient (pvalue
) in the last column.
refvar
: a value of estimated random effects.
gamma
: vector with values of the estimated gamma for each domains.
mse_FHme
data(dataME) data(datamix) sae.me <- FHme(formula = y ~ x.hat, vardir = vardir, var.x = c("var.x"), data = dataME) sae.mix <- FHme(formula = y ~ x.hat1 + x.hat2 + x3 + x4, vardir = vardir, var.x = c("var.x1", "var.x2"), type.x = "mix", data = datamix)
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