Compromise Allocation in Univariate Stratified Sampling

Park, Hyeonah; Na, Seongryong; Jeon, Jongwoo

doi:10.1080/03610920600974609

Cited by 5 publications

(8 citation statements)

References 7 publications

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“…The approach considered by Park et al (2007) is summarized here for the sake of continuity in univariate case and to formulate the problem for its multivariate case.…”

Section: The Solution: the Univariate Casementioning

confidence: 99%

“…They also showed that under certain conditions their allocation outperforms in comparison to modified Neyman allocation and proportional allocation. Ansari et al (2011) justified the assumption of the equality of some of the stratum variances as considered by the Park et al (2007). Practically, there may be circumstances that allow this assumption.…”

Section: Introductionmentioning

confidence: 99%

“…Suppose that a population of size N has stratified into L non-overlapping and exhaustive strata of sizes where h n are called as the Modified Neyman allocation (see Sukhatme et al (1984)). During stratification some strata variances are unknown but may be assumed with equal variances, as discussed by Park et al (2007). They obtained an allocation by using estimated pooled standard deviations and proportional allocation for combined strata.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

An Optimum Multivariate-Multiobjective Stratified Sampling Design: Fuzzy Programming Approach

Varshney¹,

Gupta²,

Ali³

2017

Pak.j.stat.oper.res.

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In stratified sampling design when the cost of measuring the units is not significant in each stratum, the estimation of population mean or total constructed from a selected sample according to Neyman allocation is advisable. In general the practical use of Neyman allocation suffers from a number of limitations, when there is no information about strata standard deviations except about the equality of standard deviations between some of the strata, then the precision of the estimate may be increased by pooling the strata with equal standard deviations as a single stratum and the problem of allocation is resolved by using Neyman and proportional allocations simultaneously. In this paper the case of multiple pooling of the standard deviations of the estimates in a multivariate stratified sampling for more than three strata. The problem is formulated as a Multiobjective Nonlinear Programming Problem and its solution procedure is suggested by using Fuzzy Programming approach.

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“…The approach considered by Park et al (2007) is summarized here for the sake of continuity in univariate case and to formulate the problem for its multivariate case.…”

Section: The Solution: the Univariate Casementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

An Optimum Multivariate-Multiobjective Stratified Sampling Design: Fuzzy Programming Approach

Varshney¹,

Gupta²,

Ali³

2017

Pak.j.stat.oper.res.

View full text Add to dashboard Cite

show abstract

“…Park et al (2007) have considered a simple situation where two of three strata have an equal standard deviation.…”

Section: Optimum Allocation Using Pooled Standard Deviation Among Stratamentioning

confidence: 99%

“…The lower bound of the size of preliminary samples to estimate strata standard deviations for optimum allocation was presented by Sukhatme and Sukhatme (1970). Park et al (2007) proposed a method of compromise allocation where optimum allocation using estimated pooled standard deviation is first employed and proportional allocation is used within the combined strata.…”

Section: Introductionmentioning

confidence: 99%