• 제목/요약/키워드: sample p-quantile

검색결과 4건 처리시간 0.017초

Quantile Estimation in Successive Sampling

  • Singh, Housila P.;Tailor, Ritesh;Singh, Sarjinder;Kim, Jong-Min
    • Proceedings of the Korean Association for Survey Research Conference
    • /
    • 한국조사연구학회 2006년도 추계학술대회 발표논문집
    • /
    • pp.67-83
    • /
    • 2006
  • In successive sampling on two occasions the problem of estimating a finite population quantile has been considered. The theory developed aims at providing the optimum estimates by combining (i) three double sampling estimators viz. ratio-type, product-type and regression-type, from the matched portion of the sample and (ii) a simple quantile based on a random sample from the unmatched portion of the sample on the second occasion. The approximate variance formulae of the suggested estimators have been obtained. Optimal matching fraction is discussed. A simulation study is carried out in order to compare the three estimators and direct estimator. It is found that the performance of the regression-type estimator is the best among all the estimators discussed here.

  • PDF

QUANTILE ESTIMATION IN SUCCESSIVE SAMPLING

  • Singh, Housila P.;Tailor, Ritesh;Singh, Sarjinder;Kim, Jong-Min
    • Journal of the Korean Statistical Society
    • /
    • 제36권4호
    • /
    • pp.543-556
    • /
    • 2007
  • In successive sampling on two occasions the problem of estimating a finite population quantile has been considered. The theory developed aims at providing the optimum estimates by combining (i) three double sampling estimators viz. ratio-type, product-type and regression-type, from the matched portion of the sample and (ii) a simple quantile based on a random sample from the unmatched portion of the sample on the second occasion. The approximate variance formulae of the suggested estimators have been obtained. Optimal matching fraction is discussed. A simulation study is carried out in order to compare the three estimators and direct estimator. It is found that the performance of the regression-type estimator is the best among all the estimators discussed here.

A Confidence Interval for Median Survival Time in the Additive Risk Model

  • Kim, Jinheum
    • Journal of the Korean Statistical Society
    • /
    • 제27권3호
    • /
    • pp.359-368
    • /
    • 1998
  • Let ξ$_{p}$(z$_{0}$) be the pth quantile of the distribution of the survival time of an individual with time-invariant covariate vector z$_{0}$ in the additive risk model. We propose an estimator of (ξ$_{p}$(z$_{0}$) and derive its asymptotic distribution, and then construct an approximate confidence interval of ξ$_{p}$(z$_{0}$) . Simulation studies are carried out to investigate performance of the proposed estimator far practical sample sizes in terms of empirical coverage probabilities. Also, the estimator is illustrated on small cell lung cancer data taken from Ying, Jung, and Wei (1995) .d Wei (1995) .

  • PDF