کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
6869874 | 681514 | 2014 | 18 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Statistical inference for population quantiles and variance in judgment post-stratified samples
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
نظریه محاسباتی و ریاضیات
پیش نمایش صفحه اول مقاله
چکیده انگلیسی
A judgment post-stratified (JPS) sample is used in order to develop statistical inference for population quantiles and variance. For the pth order of the population quantile, a test is constructed, an estimator is developed, and a distribution-free confidence interval is provided. An unbiased estimator for the population variance is also derived. For finite sample sizes, it is shown that the proposed inferential procedures for quantiles are more efficient than corresponding simple random sampling (SRS) procedures, but less efficient than corresponding ranked set sampling (RSS) procedures. The variance estimator is less efficient, as efficient as, or more efficient than a simple random sample variance estimator for small, moderately small, and large sample sizes, respectively. Furthermore, it is shown that JPS sample quantile estimators and tests are asymptotically equivalent to RSS estimators and tests in their efficiency comparison.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Computational Statistics & Data Analysis - Volume 77, September 2014, Pages 188-205
Journal: Computational Statistics & Data Analysis - Volume 77, September 2014, Pages 188-205
نویسندگان
Omer Ozturk,