sae-class {hbsae} | R Documentation |
S3 class for the fitted model and SAE outcomes.
Description
Functions fSAE
, fSurvReg
, fSAE.Area
and fSAE.Unit
return an object of class sae
. It contains information on the model fit as well as the
small area estimates, error estimates and a few model selection measures.
The functions listed below extract the main components from an object of class sae
.
EST(x, type="sae", tot=FALSE)
return the vector of small area estimates of
sae
object x. Alternatively, withtype
"coef" or "raneff" fixed or random effect estimates are returned. If 'tot=TRUE' and 'type="sae"' estimates for area population totals instead of means are returned.MSE(x, type="sae", tot=FALSE)
return the vector of mean squared errors of
sae
object x. Alternatively, withtype
"coef" or "raneff" MSEs of fixed or random effects are returned. If 'tot=TRUE' and 'type="sae"' MSEs for area population totals instead of means are returned.SE(x, type="sae", tot=FALSE)
extract standard errors, i.e. square roots of MSEs.
RMSE(x, type="sae", tot=FALSE)
alias for SE(x, type="sae", tot=FALSE)
relSE(x, type="sae")
extract relative standard errors.
COV(x)
extract the covariance matrix for the small area estimates.
COR(x)
extract the correlation matrix for the small area estimates.
coef(x)
coef
method forsae
objects; returns vector of fixed effects.vcov(x)
vcov
method forsae
objects; returns covariance matrix for fixed effects.raneff(x, pop)
return vector of random effects. If
pop=TRUE
returns a vector for predicted areas (zero for out-of-sample areas), otherwise a vector for in-sample areas.raneff.se(x, pop)
return vector of standard errors for random effects.
residuals(x)
residuals
method forsae
objects; returns a vector of residuals.fitted(x)
fitted
method forsae
objects; returns a vector of fitted values.se2(x)
extracts within-area variance estimate.
sv2(x)
extracts between-area variance estimate.
wDirect(x, pop)
extract vector of weights of the survey regression components in the small area estimates. If
pop=TRUE
returns a vector for predicted areas (zero for out-of-sample areas), otherwise a vector for in-sample areas.synthetic(x)
extract vector of synthetic estimates.
CV(x)
extract leave-one-out cross-validation measure.
cAIC(x)
extract conditional AIC measure.
R2(x)
extract unit-level R-squared goodness-of-fit measure.
Other components include
relErrM,relErrV
relative numerical integration errors in estimates and MSEs, for
method
"HB".
Examples
d <- generateFakeData()
# compute small area estimates
sae <- fSAE(y0 ~ x + area2, data=d$sam, area="area", popdata=d$Xpop)
coef(sae) # fixed effects
raneff(sae) # random effects
sv2(sae) # between-area variance
se2(sae) # within-area variance
cAIC(sae) # conditional AIC