A modified estimator of population mean using power transformation

Singh, Housila P.; Tailor, Rajesh; Singh, Sarjinder; Kim, Jong Min

doi:10.1007/s00362-006-0371-2

Cited by 71 publications

(60 citation statements)

References 5 publications

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“…Motivated by Singh et al [13], we define a modified exponential type estimator for estimating Y in the stratified random sampling as…”

Section: Proposed Exponential Estimatormentioning

confidence: 99%

Modified Exponential Type Estimator for Population Mean Using Auxiliary Variables in Stratified Random Sampling

Özel

2015

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Technology's perpetual vicissitude and product models' distinction in industrial market have a crucial effect on forecasting demand for spare components. In order to set forth the future demand rates for products, inventory managers repetitively update their prognostications. Bayesian model is utilizing a prior probability distribution for the injunctive authorization rate which was habituated in order to get optimum levels of account over a number of periods. However, under sundry demand rates like intermittent demand, Bayesian Model's performance has not been analyzed. With the help of a research question, the study investigates that circumstance. Keywords: Stratified random sampling, exponential type estimates, Auxiliary information, Mean squared error, Efficiency Jel Code: C10 TABAKALI RASGELE ÖRNEKLEMEDE YARDIMCI DEĞİŞKENLER KULLANARAK KİTLE ORTALAMASI İÇİN DEĞİŞTİRİLMİŞ ÜSTEL TİP TAHMİN EDİCİ ÖzetBu çalışmada, kitle ortalaması için yardımcı değişken bilgisi kullanarak yeni bir üstel tip tahmin edici tabakalı örneklemede geliştirilmiştir. Elde edilen tahmin edicinin etkinliğini değerlendirebilmek için, ilk olarak literatürdeki bazı tahmin ediciler incelenmiş ve önerilen stratejinin optimum özelliği incelenmiştir. Önerilen tahmin edicinin özelliğini değerlendirebilmek için optimallik koşulu altında benzetim çalışması ve gerçek veri uygulamaları yapılmıştır. Sonuçlar elde edilen tahmin edicinin var olan oran ve çarpım tahmin edicilerinden ve tabakalı örnekleme düzeninde yansız tahmin ediciden daha etkin olduğunu göstermiştir.

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“…Motivated by Singh et al [13], we define a modified exponential type estimator for estimating Y in the stratified random sampling as…”

Section: Proposed Exponential Estimatormentioning

confidence: 99%

Modified Exponential Type Estimator for Population Mean Using Auxiliary Variables in Stratified Random Sampling

Özel

2015

Alphanumeric

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“…On this issue extensive work has been done using auxiliary information such as population median, mean, quartiles, deciles, coefficient of variation, coefficient of correlation, coefficient of skewness and coefficient of kurtosis etc. As a solution of this issue various estimator(s) or classes of estimators have been proposed to get improved results by several authors including Sisodia and Dwivedi [2], Upadhyaya and Singh [3], Singh and Tailor [4], Kadilar and Cingi [5,6], Singh et al [7,8], Gupta and Shabbir [9], Koyuncu and Kadilar [10,11], Yan and Tian [12], Haq and Shabbir [13], Singh and Solanki [14], Yadav and Kadilar [15], Subramani and Kumarapandiyan [16,17], Subramani and Prabavathy [18], Yadav et al [19], Khan et al [20], Kumar [21], Irfan et al [22], Walia et al [23] and many more.…”

Section: Introductionmentioning

confidence: 99%

Efficient Ratio-Type Estimators of Finite Population Mean Based on Correlation Coefficient

2017

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“…This work is focused on improving the efficiency of some ratio cum product estimators in the literature by obtaining the optimal value. Cochran (1940), Singh, Tailor and Kakran (2004), Cingi (2004, 2006), Subramani (2013), Subramani andKumarapandiyan (2012a, 2012b), Subramani andMaster Ajith (2016a, 2016b), Upadhyaya and Singh (1999), Yan and Tian (2010), Sisodia and Dwivedi (1981), etc. suggested different class of estimators of the population mean with known parameters of the auxiliary variable.…”

Section: Introductionmentioning

confidence: 99%

Almost Unbiased Ratio cum Product Estimator for Finite Population Mean with Known Median in Simple Random Sampling

Subramani

Master

2017

Nep. J. Stats.

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Introduction: In sampling theory, different procedures are used to obtain the efficient estimator of the population mean. The commonly used method is to obtain the estimator of the population mean is simple random sampling without replacement when there is no auxiliary variable is available. There are methods that use auxiliary information of the study characteristics. If the auxiliary variable is correlated with study variable, number of estimators are widely available in the literature.Objective: This study deals with a new ratio cum product estimator is developed for the estimation of population mean of the study variable with the known median of the auxiliary variable in simple random sampling.Materials and Methods: The bias and mean squared error of proposed estimator are derived and compared with that of the existing estimators by analytically and numerically.Results: The proposed estimator is less biased and mean squared error is less than that of the existing estimators and from the numerical study, under some known natural populations, the bias of proposed estimator is approximately zero and the mean squared error ranged from 6.83 to 66429.21 and percentage relative efficiencies ranged from 103.65 to 2858.75.Conclusion: The proposed estimator under optimum conditions is almost unbiased and performs better than all other existing estimators.Nepalese Journal of Statistics, 2017, Vol. 1, 1-14

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A modified estimator of population mean using power transformation

Abstract: Study variate, auxiliary variate, mean squared error, efficiency,

Cited by 71 publications

References 5 publications

Modified Exponential Type Estimator for Population Mean Using Auxiliary Variables in Stratified Random Sampling

Modified Exponential Type Estimator for Population Mean Using Auxiliary Variables in Stratified Random Sampling

Efficient Ratio-Type Estimators of Finite Population Mean Based on Correlation Coefficient

Almost Unbiased Ratio cum Product Estimator for Finite Population Mean with Known Median in Simple Random Sampling

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