Ranked set sampling theory with selective probability vector
type: Item
instance of: scholarly article
title: Ranked set sampling theory with selective probability vector
zbMATH Open document ID: 0542.62003
DOI: 10.1016/0378-3758(83)90035-6
author: Shan-Huo Chen
published in: Journal of Statistical Planning and Inference
publication date: 1983-01-01T00:00:00Z
review text: In this paper, the author has given an estimator using the concept of selective probability vector to estimate the population mean, and has discussed its properties using the optimization techniques of linear programming.
reviewed by: B.K.Taneja
Mathematics Subject Classification ID: 62D05
Mathematics Subject Classification ID: 62F07
Mathematics Subject Classification ID: 62G30
Mathematics Subject Classification ID: 90C90
zbMATH DE Number: 3862209
zbMATH Keywords: ranked set sampling
zbMATH Keywords: condition of unbiasedness
zbMATH Keywords: order statistics
zbMATH Keywords: linear programming
zbMATH Keywords: selective probability vector
zbMATH Keywords: optimization
MaRDI profile type: Publication
full work available at URL: 0378-3758(83)90035-6
OpenAlex ID: W2001362868
cites work: Q5629053
cites work: Ranked Set Sampling Theory with Order Statistics Background
cites work: Practical note on estimation of population means based on samples stratified by means of ordering
cites work: On unbiased estimates of the population mean based on the sample stratified by means of ordering
cites work: The MG-procedure in ranked set sampling
cites work: RANKED SET SAMPLING THEORY WITH SELECTIVE PROBABILITY MATRIX1
Recommended article: Ranked set sampling. Theory and applications
Recommended article: On the theory of ranked-set sampling and its ramifications
Recommended article: Random selection in ranked set sampling and its applications
Recommended article: Ranked Set Sampling with Size-Biased Probability of Selection
Recommended article: Q3570252
Recommended article: Theory & Methods: Selected Ranked Set Sampling
description: scientific article; zbMATH DE number 3862209