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Confidence intervals for quantile estimation using jackknife techniques. (English) Zbl 1223.62004

Population quantile estimation is considered by a finite sample when some auxiliary information is available. Ratio, regression and differences estimators are discussed. A jackknife technique is described for bias correction and variance estimation of quantile estimators. Conditions for asymptotic normality of these estimates are given. Confidence intervals are constructed for quantiles based on the asymptotic normality and jackknife variance estimates. Numerical results are presented for simulated samples from real life finite populations.

MSC:

62D05 Sampling theory, sample surveys
62F25 Parametric tolerance and confidence regions
62F40 Bootstrap, jackknife and other resampling methods
62G15 Nonparametric tolerance and confidence regions
62G09 Nonparametric statistical resampling methods
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