Novel imputation methods under stratified simple random sampling

被引：3

作者：

Kumar, Anoop ^{[1
]}

Bhushan, Shashi ^{[2
]}

Mustafa, Manahil SidAhmed ^{[3
]}

Aldallal, Ramy ^{[4
]}

Aljohani, Hassan M. ^{[5
]}

Almulhim, Fatimah A. ^{[6
]}

机构：

[1] Cent Univ Haryana, Dept Stat, Mahendergarh 123031, India

[2] Univ Lucknow, Dept Stat, Lucknow 226007, UP, India

[3] Univ Tabuk, Fac Sci, Dept Stat, Tabuk, Saudi Arabia

[4] Prince Sattam Bin Abdulaziz Univ, Coll Business Adm Hawtat Bani Tamim, Dept Management, Al Hulwah, Saudi Arabia

[5] Taif Univ, Coll Sci, Dept Math & Stat, POB 11099, Taif 21944, Saudi Arabia

[6] Princess Nourah Bint Abdulrahman Univ, Coll Sci, Dept Math Sci, POB 84428, Riyadh 11671, Saudi Arabia

来源：

ALEXANDRIA ENGINEERING JOURNAL | 2024年 / 95卷

关键词：

Missing values; Imputation; Stratified simple random sampling; ESTIMATORS; RATIO;

D O I：

10.1016/j.aej.2024.03.088

中图分类号：

T [工业技术];

学科分类号：

08 ;

摘要：

This paper addresses some classes of combined and separate imputation methods (CSIMs) of the population mean under stratified simple random sampling (SSRS) along with their characteristics. To the best of our knowledge, these imputation methods (IMs) have yet not been studied by any author under SSRS, hence these IMs are called 'novel'. In addition, the existing CSIMs are distinguished as the members of the suggested CSIMs, respectively. The theoretical conditions under which the proposed IMs perform better are obtained by comparing the proposed IMs with the existing IMs. To validate the theoretical findings, the numerical and simulation studies are conducted on real and artificial populations, respectively.

引用

页码：236 / 246

页数：11

共 50 条

[21] Imputation methods for quantile estimation under missing at random
Yang, Shu
Kim, Jae-Kwang
Shin, Dong Wan
STATISTICS AND ITS INTERFACE, 2013, 6 (03) : 369 - 377
[22] IMPROVEMENT OVER TRADITIONAL METHODS OF ESTIMATION IN STRATIFIED RANDOM SAMPLING
Saini, Monika
Kumar, Ashish
INTERNATIONAL JOURNAL OF AGRICULTURAL AND STATISTICAL SCIENCES, 2019, 15 (02): : 643 - 648
[23] Discrete Weibull distribution: different estimation methods under ranked set sampling and simple random sampling
Taconeli, Cesar Augusto
Rodrigues de Lara, Idemauro Antonio
JOURNAL OF STATISTICAL COMPUTATION AND SIMULATION, 2022, 92 (08) : 1740 - 1762
[24] Estimation of finite population mean in simple random sampling and stratified random sampling using two auxiliary variables
Muneer, Siraj
Shabbir, Javid
Khalil, Alamgir
COMMUNICATIONS IN STATISTICS-THEORY AND METHODS, 2017, 46 (05) : 2181 - 2192
[25] The effectiveness of simple and stratified random sampling in broadcast news content analysis
Riffe, D
Lacy, S
Nagovan, J
Burkum, L
JOURNALISM & MASS COMMUNICATION QUARTERLY, 1996, 73 (01) : 159 - 168
[26] Environmental sampling with a concomitant variable: A comparison between ranked set sampling and stratified simple random sampling
Kaur, A
Patil, GP
Shirk, SJ
Taillie, C
JOURNAL OF APPLIED STATISTICS, 1996, 23 (2-3) : 231 - 255
[27] An efficient exponential estimator of the mean under stratified random sampling
Zaman, Tolga
MATHEMATICAL POPULATION STUDIES, 2021, 28 (02) : 104 - 121
[28] Calibrated Estimator for Sensitive Variables under Stratified Random Sampling
Jabeen, Riffat
Aslam, Muhammad Kamran
Sanaullah, Aamir
Zaka, Azam
THAILAND STATISTICIAN, 2024, 22 (02): : 363 - 373
[29] Estimation of finite population variance under stratified random sampling
Haq, Abdul
Usman, Muhammad
Khan, Manzoor
COMMUNICATIONS IN STATISTICS-SIMULATION AND COMPUTATION, 2023, 52 (12) : 6193 - 6209
[30] Finite population distribution function estimation with dual use of auxiliary information under simple and stratified random sampling
Hussain, Sardar
Ahmad, Sohaib
Saleem, Mariyam
Akhtar, Sohail
PLOS ONE, 2020, 15 (09):

← 1 2 3 4 5 →