A Class of Improved Estimators for Estimating Population Mean Regarding Partial Information in Double Sampling

A Class of Improved Estimators for Estimating Population Mean Regarding Partial Information in Double Sampling

Aamir Sanaullah

Contact

Dr. Saleha Shouket

Contact

Hina Khan

Contact

Government College University, Lahore

A Class of Improved Estimators for Estimating Population Mean Regarding Partial Information in Double Sampling

Article Fingerprint

ReserarchID

L81YR

A Class of Improved Estimators for Estimating Population Mean Regarding Partial Information in Double Sampling Banner

AI TAKEAWAY

Connecting with the Eternal Ground

Abstract

In this paper a class of improved estimators has been proposed for estimating population mean in two phase (double) sampling when only partial information is available on either of two auxiliary variables. Under simple random sampling (SRWOR), expressions of mean square error and bias have been derived to make comparison of suggested class with wide range of other estimators. Empirical study has also been given using five different natural populations. Empirical study confirmed that the suggested class of improved estimators is more efficient under percent relative efficiency (PRE) criterion.

References

42 Cites in Article

Reference Format

J Armstrong,H St-Jean (1993). Generalized regression estimator for a twophase sample of tax records.
P Bedi (1985). On two-phase multivariate sampling estimator.
A Bowley (1926). The Influence on the Precision of Index-Numbers of Correlation Between the Prices of Commodities.
L Chand (1975). Some Ratio-type Estimators based on two or more Auxiliary Variables.
Mir Rahaman,Subhrajyoti Sengupta,Monami Sarkar,Jyotshna Sarkar,Debanjan Baul,Rajdeep Mallick,Asit Mandal,Arup Chattopadhyay (1988). Diversity analysis of long- and round-fruited brinjal genotypes using multivariate analysis.
A Das,T Tripathi (1978). Use of auxiliary information in estimating the finite population variance.
F Freese (1962). Elementary forest sampling.
Morris Hansen,William Hurwitz (1943). On the Theory of Sampling from Finite Populations.
B Kiregyera (1980). A chain ratio-type estimator in finite population double sampling using two auxiliary variables.
B Kiregyera (1984). Regression-type estimators using two auxiliary variables and the model of double sampling from finite populations.
S Mohanty (1967). Combination of Regression and Ratio Estimate.
Rahul Mukerjee,T Rao,K Vijayan (1987). Regression Type Estimators Using Multiple Auxiliary Information.
Jerzy Neyman (1934). On the Two Different Aspects of the Representative Method: The Method of Stratified Sampling and the Method of Purposive Selection.
Jerzy Neyman (1938). Contribution to the theory of sampling human populations..
B Pandey,Dubey,Vyas (1988). Modified product estimator using coefficient of variation of auxiliary variate.
D Roy (2003). A regression type estimates in two-phase sampling using two auxiliary variables.
L Sahoo,G Mishra,S Nayak (1993). On two different classes of estimators in two-phase sampling using multi-auxiliary variables.
J Sahoo,L Sahoo,S Mohanty (1994). A regression approach to estimation in two-phase sampling using two auxiliary variables.
J Sahoo,L Sahoo,S Mohanty (1994). An alternative approach to estimation in two-phase sampling using two auxiliary variables.
M Samiuddin,M Hanif (2007). Estimation of population mean in single and two phase sampling with or without additional information.
Donald Searls (1964). The Utilization of a Known Coefficient of Variation in the Estimation Procedure.
A Sen (1978). Estimation of the population mean when the coefficient of variation is known.
H Singh,R Tailor (2003). Use of known correlation coefficient in estimating the finite population mean.
H Singh,S Singh,Kim Jong-Min (2006). General families of chain ratio type Estimators of the population mean with Known coefficient of variation of the Second auxiliary variable in two phase Sampling.
H Singh,R Tailor,M Kakaran (2004). An estimator of Population mean using power transformation.
R Singh,P Chauhan,N Swan,F Smarandache (2011). Unknown Title.
G Singh (2001). On the use of transformed auxiliary variable in the estimation of population mean in two phase sampling.
G Singh (2003). On the improvement of product method of estimation in sample surveys.
Housila Singh,Gajendra Vishwakarma (2008). A general procedure for estimating the population mean in stratified sampling using auxiliary information.
Housila Singh,Nidhi Mathur,Prem Chandra (2004). A CHAIN-TYPE ESTIMATOR FOR POPULATION VARIANCE USING TWO AUXILIARY VARIABLES IN TWO-PHASE SAMPLING.
J Singh,B Pandey,K Hirano (1973). On the utilization of a known coefficient of kurtosis in the estimation procedure of variance.
R Singh,P Chuhan,N Sawan (2007). A Family of Estimators for Estimating Population Mean Using Known Correlation Coefficient in Two Phase Sampling.
B Sisodia,V Dwivedi (1981). A modified ratio estimator using coefficient of variation of auxiliary variable.
George Snedecor,Arnold King (1942). Recent Developments in Sampling for Agricultural Statistics.
S Spurr (1952). <i>Forest Ecology.</i> By Stephen H. Spurr. (New York: Ronald Press, 1964. 352 pp. Illustrations, index, bibliography. $8.50).
S Srivastava,Rani,B Khare,S Srivastava (1990). A generalized chain ratio estimator for mean of finite population.
S Srivastava,H Jhajj (1980). A class of estimators using auxiliary information for estimating finite population variance.
Balkrishna Sukhatme (1962). Some Ratio-Type Estimators in Two-Phase Sampling.
Neha Sharma,Reecha Sharma,Neeru Jindal (1970). Age Estimation and its Progression from Face Images.
N Unnikrishan,S Kunte (1995). Optimality of an analogue of Basu's estimator under a double sampling design.
L Upadhyaya,G Singh (2001). Chain type estimators using transformed auxiliary variable in two-phase sampling.
L Upadhyaya,H Singh (1999). Use of transformed auxiliary variable in estimating the finite population mean.

Download References

Funding

No external funding was declared for this work.

Conflict of Interest

The authors declare no conflict of interest.

Ethical Approval

No ethics committee approval was required for this article type.

Data Availability

Not applicable for this article.

How to Cite This Article

Aamir Sanaullah. 2013. \u201cA Class of Improved Estimators for Estimating Population Mean Regarding Partial Information in Double Sampling\u201d. Global Journal of Science Frontier Research - F: Mathematics & Decision GJSFR-F Volume 12 (GJSFR Volume 12 Issue F14): .

More Citation Formats

Select Citation Style:

Download Citation

Download Article

GJSFR Volume 12 Issue F14
Pg. 33- 45

Explore Journals Explore Volume Read This Issue

Journal Specifications

Crossref Journal DOI 10.17406/GJSFR

Print ISSN 0975-5896

e-ISSN 2249-4626

Keywords

auxiliary variable Bias double sampling Mean square error partial information

Submission ReceivedOctober 15, 2012
Peer Review Double Blind
Handling Editor
Accepted November 8, 2012
Published November 20, 2012

Version of record

v1.2

Issue date

January 5, 2013

Language

Experiance in AR

Explore published articles in an immersive Augmented Reality environment. Our platform converts research papers into interactive 3D books, allowing readers to view and interact with content using AR and VR compatible devices.

View in VR

Read in 3D

Your published article is automatically converted into a realistic 3D book. Flip through pages and read research papers in a more engaging and interactive format.

View in 3D

Article Matrices

Total Score: 108

Country: Pakistan

Subject: Global Journal of Science Frontier Research - F: Mathematics & Decision

Authors: Dr. Saleha Shouket, Hina Khan, Aamir Sanaullah (PhD/Dr. count: 1)

View Count (all-time): 155

Total Views (Real + Logic): 5089

Total Downloads (simulated): 2679

Publish Date: 2013 01, Sat

Monthly Totals (Real + Logic):

Month 1: 35 views
Month 2: 61 views
Month 3: 35 views
Month 4: 20 views
Month 5: 58 views
Month 6: 38 views
Month 7: 37 views
Month 8: 46 views
Month 9: 42 views
Month 10: 51 views
Month 11: 27 views
Month 12: 45 views
Month 13: 37 views
Month 14: 35 views
Month 15: 16 views
Month 16: 32 views
Month 17: 38 views
Month 18: 37 views
Month 19: 34 views
Month 20: 29 views
Month 21: 21 views
Month 22: 23 views
Month 23: 21 views
Month 24: 16 views
Month 25: 14 views
Month 26: 27 views
Month 27: 38 views
Month 28: 33 views
Month 29: 39 views
Month 30: 27 views
Month 31: 21 views
Month 32: 31 views
Month 33: 34 views
Month 34: 38 views
Month 35: 33 views
Month 36: 20 views
Month 37: 34 views
Month 38: 29 views
Month 39: 30 views
Month 40: 21 views
Month 41: 30 views
Month 42: 49 views
Month 43: 35 views
Month 44: 39 views
Month 45: 23 views
Month 46: 27 views
Month 47: 29 views
Month 48: 15 views
Month 49: 43 views
Month 50: 36 views
Month 51: 28 views
Month 52: 12 views
Month 53: 32 views
Month 54: 27 views
Month 55: 33 views
Month 56: 35 views
Month 57: 23 views
Month 58: 21 views
Month 59: 18 views
Month 60: 34 views
Month 61: 28 views
Month 62: 24 views
Month 63: 32 views
Month 64: 29 views
Month 65: 24 views
Month 66: 24 views
Month 67: 34 views
Month 68: 48 views
Month 69: 22 views
Month 70: 20 views
Month 71: 35 views
Month 72: 41 views
Month 73: 38 views
Month 74: 37 views
Month 75: 35 views
Month 76: 17 views
Month 77: 38 views
Month 78: 35 views
Month 79: 29 views
Month 80: 28 views
Month 81: 31 views
Month 82: 25 views
Month 83: 13 views
Month 84: 19 views
Month 85: 45 views
Month 86: 37 views
Month 87: 23 views
Month 88: 42 views
Month 89: 34 views
Month 90: 37 views
Month 91: 17 views
Month 92: 32 views
Month 93: 34 views
Month 94: 28 views
Month 95: 26 views
Month 96: 47 views
Month 97: 40 views
Month 98: 46 views
Month 99: 40 views
Month 100: 30 views
Month 101: 26 views
Month 102: 35 views
Month 103: 24 views
Month 104: 31 views
Month 105: 13 views
Month 106: 25 views
Month 107: 34 views
Month 108: 38 views
Month 109: 26 views
Month 110: 26 views
Month 111: 24 views
Month 112: 20 views
Month 113: 29 views
Month 114: 31 views
Month 115: 31 views
Month 116: 40 views
Month 117: 21 views
Month 118: 10 views
Month 119: 19 views
Month 120: 25 views
Month 121: 29 views
Month 122: 26 views
Month 123: 43 views
Month 124: 23 views
Month 125: 39 views
Month 126: 36 views
Month 127: 22 views
Month 128: 41 views
Month 129: 34 views
Month 130: 25 views
Month 131: 25 views
Month 132: 23 views
Month 133: 41 views
Month 134: 30 views
Month 135: 25 views
Month 136: 34 views
Month 137: 22 views
Month 138: 33 views
Month 139: 33 views
Month 140: 25 views
Month 141: 37 views
Month 142: 19 views
Month 143: 33 views
Month 144: 34 views
Month 145: 22 views
Month 146: 36 views
Month 147: 31 views
Month 148: 23 views
Month 149: 28 views
Month 150: 42 views
Month 151: 30 views
Month 152: 38 views
Month 153: 37 views
Month 154: 28 views
Month 155: 30 views
Month 156: 22 views
Month 157: 30 views
Month 158: 44 views
Month 159: 41 views
Month 160: 60 views
Month 161: 29 views

Total Views: 5089

Total Downloads: 2679

2026 Trends

Published Article

Our website is actively being updated, and changes may occur frequently. Please clear your browser cache if needed. For feedback or error reporting, please email [email protected]