Estimation of Domain Mean Using Conventional Synthetic Estimator with Two Auxiliary Characters

Ashutosh, .

doi:10.1007/s40745-020-00287-9

Cited by 2 publications

(3 citation statements)

References 7 publications

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“…Some of the noble works for domain estimation vie calibration approach have been discussed by Ekaette and Etebong, 20 Iseh and Enang, 21 and Ashutosh. 22,23 Calibration estimation of domain based on the model idea has been given by Wu and Sitter. 24 Recently, Rao and Molina 17 have contributed to the model based through different weight functions.…”

Section: Many Availablementioning

confidence: 99%

“…Hence, we are taking a reliable sample (approximately 50%) 100 size by each domain and it is denoted by x ′ a . The formula of the conventional indirect calibration generalized regression estimator and conventional Nguyen and conventional indirect for domain total using two phase sampling with the help of Equations ( 22) and (23). If replaced T s L,a = T IL,a , T s L,a = T s IL,a , and T L,a = T GREG,a , T Ratio,a , T Nguyen,a, and T Power,a .…”

Section: Simulation Study In the Second Situationmentioning

confidence: 99%

“…However, various direct and indirect domain estimation using auxiliary variable has been discussed and tested their performances empirical by Tikkiwal et al 19 The sensitivity of the auxiliary variable(s) has also played a significant role during estimates of the weight of the estimator. Some of the noble works for domain estimation vie calibration approach have been discussed by Ekaette and Etebong, 20 Iseh and Enang, 21 and Ashutosh 22,23 . Calibration estimation of domain based on the model idea has been given by Wu and Sitter 24 .…”

Section: Introductionmentioning

confidence: 99%

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Simulation study of small domain with calibration approach

Ashutosh

Shahzad

Al‐Noor

et al. 2022

Concurrency and Computation

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Some of the flexible models are available in the statistics literature are exponential and power distribution. They are very helpful in the modeling for situations when the shape and distribution of interested variables are positively skewed. We are presenting the calibration based estimates of domain total for exponential and the power model under such prevailing circumstances. Two different situations are considered:(i) domain total of the auxiliary variable is known and (ii) domain total of the auxiliary variable is unknown. To overcome the difficulties, to get calibration weights under second situation, two phase sampling technique is utilized. The Newton-Raphson method of approximation is used to estimate the Lagrange's multiplier. In addition, the efficiency of the proposed estimator has been given with support of the proposed weights under shortest Chi-square distance function. A numerical value based on the simulation study in terms of absolute relative bias and simulated relative standard error have been given using a real data of the Sweden municipality 1984 for comparison of the estimators. Finding shows that the proposed power function based calibration estimator is more efficient than the existing calibration based estimators of the domain total in both the situations.

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