id: 06135681
dt: j
an: 
au: Chandra, Hukum; Sud, U.C.
ti: Small area estimation for zero-inflated data.
so: Commun. Stat., Simulation Comput. 41, No. 5, 632-643 (2012).
py: 2012
pu: Taylor \& Francis, Philadelphia, PA
la: EN
cc: 62D05
ut: bootstrap method; mean squared error; mixture model; small area estimation;
    zero-inflated data
ci: 
li: doi:10.1080/03610918.2011.598991
ab: Summary: The commonly used method of small area estimation (SAE) under a
    linear mixed model may not be efficient if data contain substantial
    proportion of zeros than would be expected under standard model
    assumptions (hereafter zero-inflated data). The authors discuss the SAE
    for zero-inflated data under a two-part random effects model that
    account for excess zeros in the data. Empirical results show that
    proposed method for SAE works well and produces an efficient set of
    small area estimates. An application to real survey data from the
    National Sample Survey Office of India demonstrates the satisfactory
    performance of the method. The authors describe a parametric bootstrap
    method to estimate the mean squared error (MSE) of the proposed
    estimator of small areas. The bootstrap estimates of the MSE are
    compared to the true MSE in simulation study.
rv: