Estimation of Population Mean in Sample Surveys using Auxiliary Information when it Lacks Temporization


1 / 3

Authors

  • Shalabh Indian Institute of Technology Kanpur, Kanpur
  • Subhra Sankar Dhar Indian Institute of Technology Kanpur, Kanpur

https://doi.org/10.56093/jisas.v80i01.182016

Keywords:

: Population mean; Temporization effect; Auxiliary information; Ratio method; Regression method.

Abstract

An important feature in estimating the population mean in sample surveys is the use of either current observations or past information, which is 
available as auxiliary information. The ratio and regression methods of estimation are popular approaches for estimating the population mean using 
auxiliary information. In most of these surveys, the auxiliary information is available from the past and may change over time when used. This paper 
examines how this information will affect the estimation process and how the ratio and regression estimation methods are affected by such a change 
in the auxiliary information.

Downloads

Download data is not yet available.

References

Cochran, W.G. (1991). Sampling Techniques, John Wiley.

Shalabh and Subhra Sankar Dhar (2021). “Goodness of Fit in Non

parametric Regression Modelling’’, Journal of Statistical Theory

and Practice (Invited paper for the special issue dedicated to

Professor C.R. Rao on “Celebrating the Centenary of Professor

C R Rao”) Journal of Statistical Theory and Practice, volume 15,

Article number: 18.

Shalabh, Subhra Sankar Dhar and N. Balakrishna (2021). “Goodness

of Fit in Parametric and Non-parametric Econometric Models’’ in

Optimal Decision Making in Operations Research & Statistics:

Methodologies and Applications, Editors: Leopoldo Eduardo

Ca’rdenas-Barro’n, Aquil Ahmed, Irfan Ali and Ali Akbar Shaikh,

pp. 68-91, Taylor’s & Francis, Routledge, CRC Press.

Shalabh and Subhra Sankar Dhar (2023). “Testing the Goodness of Fit

in Instrumental Variables Models” in G Families of Probability

Distributions: Theory and Applications, Editors: Mir Masoom Al,

Irfan Ali, Haitham M. Youso and Mohamed Ibrahim, Taylor’s &

Francis, CRC Press, pp. 330-343.

Shalabh, Subhra Sankar Dhar and Gaurav Garg (2025). “Robust

Measures of Goodness of Fit and Outlier Detection in Linear

Regression Models” in Statistical Outliers and Related Topics,

Editors: Mir Masoom Ali, Irfan Ali, and Haitham M. Yousof,

Taylor’s & Francis, CRC Press, pp. 462-499.

Subhra Sankar Dhar and Shalabh (2022). “GIVE Statistic for Goodness

of Fit in Instrumental Variables Models with Application to

COVID Data’’ Nature Scientific Reports, 12, 9472.

Subhra Sankar Dhar, Udita Chatterjee and Shalabh (2022). “A Note

on Asymptotic Distribution of Trimmed Mean,” Journal of the

Indian Society for Probability and Statistics, 23, pp. 327-335.

Subhra Sankar Dhar, Shalabh, Prashant Jha, and Aranyak Acharya

(2026). “Variable Selection in Multiple Nonparametric Regression

Modelling” in Advanced Mathematical Techniques Applicable in

Computational and Intelligent Systems, Editors: Sandeep Singh,

Aliakbar Montazer Haghighi, and Sandeep Dalal, Taylor’s &

Francis, CRC Press (Accepted for publication).

Sukhatme, P.V., B.V. Sukhatme, S. Sukhatme and C. Asok (1984).

Sampling Theory of Surveys with Applications, Indian Society of

Agricultural Statistics, New Delhi

Downloads

Submitted

2026-07-28

Published

2026-07-28

Issue

Section

Articles

How to Cite

Shalabh, & Subhra Sankar Dhar. (2026). Estimation of Population Mean in Sample Surveys using Auxiliary Information when it Lacks Temporization. Journal of the Indian Society of Agricultural Statistics, 80(01), 39-42. https://doi.org/10.56093/jisas.v80i01.182016
Citation