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Wild Bootstrapping in Finite Populations with Auxiliary Information
Author(s) -
Helmers Roelof,
Wegkamp Marten
Publication year - 1998
Publication title -
scandinavian journal of statistics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.359
H-Index - 65
eISSN - 1467-9469
pISSN - 0303-6898
DOI - 10.1111/1467-9469.00111
Subject(s) - mathematics , bootstrapping (finance) , studentized range , statistics , heteroscedasticity , estimator , population , resampling , confidence interval , realization (probability) , ratio estimator , econometrics , standard error , bias of an estimator , minimum variance unbiased estimator , demography , sociology
Consider a finite population u , which can be viewed as a realization of a super‐population model. A simple ratio model (linear regression, without intercept) with heteroscedastic errors is supposed to have generated u . A random sample is drawn without replacement from u . In this set‐up a two‐stage wild bootstrap resampling scheme as well as several other useful forms of bootstrapping in finite populations will be considered. Some asymptotic results for various bootstrap approximations for normalized and Studentized versions of the well‐known ratio and regression estimator are given. Bootstrap based confidence interval s for the population total and for the regression parameter of the underlying ratio model are also discussed