Open AccessLogarithmic type predictive estimators under simple random sampling
Author(s) -
Shashi Bhushan,
Anoop Kumar,
Md. Tanwir Akhtar,
Showkat Ahmad Lone
Publication year - 2022
Publication title -
aims mathematics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.329
H-Index - 15
ISSN - 2473-6988
DOI - 10.3934/math.2022668
Subject(s) - estimator , simple random sample , logarithm , mean squared error , statistics , mathematics , simple (philosophy) , sampling (signal processing) , population , estimation , population mean , computer science , demography , engineering , mathematical analysis , philosophy , systems engineering , epistemology , filter (signal processing) , computer vision , sociology
This study introduces a novel predictive estimation approach of the population mean based on logarithmic type estimators as predictor under simple random sampling. The bias and mean square error of the proffered predictive estimators are examined to the approximation of order one. The efficiency conditions are obtained and the performance of the proffered predictive estimators is examined regarding the contemporary predictive estimators existing till date. Further, a broad computational study is also administered utilizing few real and artificially rendered symmetric and asymmetric populations to exemplify the theoretical results.