An alternative to the ratio-cum-product estimator in sample surveys

Tracy, Derrick S.; Singh, Housila P.; Singh, Rajesh

doi:10.1016/0378-3758(95)00136-0

Cited by 37 publications

(27 citation statements)

References 7 publications

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“…The estimator is known as chaintype ratio estimator. This work was further extended by Kiregyera (1980Kiregyera ( , 1984, Sahoo et al (1994), Tracy et al (1996), Singh and Espejo (2007), Gupta and Shabbir (2007), Shukla et al (2012), Choudhury and Singh (2012) and among others where they proposed various chain-type ratio and regression estimators. It may be noted that the most of these estimation procedures of population mean in two-phase sampling are biased which become a serious drawback for their practical applications.…”

Section: Introductionmentioning

confidence: 91%

“…Thus, to make the class of estimators practicable, these unknown population parameters may be estimated with their respective sample estimates or from past data or guessed from experience gathered over time. Such problems are also considered by Reddy (1978), Tracy et al (1996) and .…”

Section: Minimum Variance Of Proposed Class Of Estimatormentioning

confidence: 97%

“…Therefore, unbiased versions of the proposed classes of estimators are more desirable. Motivated with this argument and influenced by the bias correction techniques of Tracy et al (1996) …”

Section: Bias Reduction For the Proposed Class Of Estimatormentioning

confidence: 99%

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Development of Efficient Estimation Technique for Population Mean in Two Phase Sampling Using Fuzzy Tools

Parichha¹,

Basu

Bandyopadhyay³

et al. 2017

Journal of Applied Mathematics, Statistics and Informatics

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The present investigation deals with the problem of estimation of population mean in two-phase (double) sampling. Utilizing information on two auxiliary variables, one chain exponential ratio and regression type estimator has been proposed and its properties are studied under two different structures of twophase sampling. To make the estimator practicable, unbiased version of the proposed strategy has also been developed. The dominance of the suggested estimator over some contemporary estimators of population mean has been established through numerical illustrations carried over the data set of some natural population and artificially generated population. Categorization of the dominance ranges of the proposed estimation strategies are deployed through defuzzification tools, which are followed by suitable recommendations. Mathematics Subject Classification 2000: 62D05

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Section: Introductionmentioning

confidence: 91%

Section: Minimum Variance Of Proposed Class Of Estimatormentioning

confidence: 97%

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Development of Efficient Estimation Technique for Population Mean in Two Phase Sampling Using Fuzzy Tools

Parichha¹,

Basu

Bandyopadhyay³

et al. 2017

Journal of Applied Mathematics, Statistics and Informatics

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show abstract

“…Thus, to use such estimators one has to use guessed or estimated values of these parameters. Guessed values of these population parameters can be obtained either from past data or experience gathered over time; see (Murthy, 1967;Reddy, 1978;Tracy et al, 1996). If such guessed values are not available then it is advisable to use sample data to estimate these parameters as suggested by (Gupta and Shabbir, 2008).…”

Section: Bias and Mean Square Errors Of The Proposed Classes Of Estimmentioning

confidence: 99%

Some Estimation Procedures in Presence of Non-Response in Two-Phase Sampling

Bandyopadhyay¹,

Singh

2015

Sri Lankan J App Stats

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“…This estimator is known as the chain-type ratio estimator. This work was further extended by Kiregyera (1980;1984), Sahoo and Sahoo (1993), Tracy, Singh, and Singh (1996), Singh and Espejo (2007), Gupta and Shabbir (2007), Dash andMishra (2011), Shukla, Pathak, andThakur (2012), and Choudhury and Singh (2012), among others, who proposed various chain-type ratio and regression estimators. It may be noted that the most of these estimation procedures of the population mean in two-phase sampling are biased which becomes a serious drawback for their practical applications.…”

Section: Introductionmentioning

confidence: 97%