| sae-class | R Documentation |
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,
with type "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,
with type "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 for sae objects; returns vector of fixed effects.
vcov(x)vcov method for sae 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 for sae objects; returns a vector of residuals.
fitted(x)fitted method for sae 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,relErrVrelative numerical integration errors in estimates and MSEs, for method "HB".
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
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