A5024772198- Survey Sampling and Estimation Techniques
- Statistical Distribution Estimation and Applications
- Statistical Methods and Bayesian Inference
- Bayesian Methods and Mixture Models
- Monetary Policy and Economic Impact
- Advanced Statistical Methods and Models
- Stock Market Forecasting Methods
- Fuzzy Systems and Optimization
- Educational Methods and Analysis
- Statistical Methods and Inference
- Global Financial Crisis and Policies
- Energy Load and Power Forecasting
- Occupational and environmental lung diseases
- Financial Risk and Volatility Modeling
- Market Dynamics and Volatility
- Education Practices and Challenges
- Global trade and economics
- Educational Leadership and Administration
- Islamic Finance and Banking Studies
- Pleural and Pulmonary Diseases
- Air Quality Monitoring and Forecasting
- Complex Systems and Time Series Analysis
- Air Quality and Health Impacts
- Neural Networks and Applications
- Advanced Statistical Process Monitoring
Hacettepe University
2014-2023
Çankırı Karatekin University
2021
Sher-e-Kashmir University of Agricultural Sciences and Technology of Jammu
2021
Sivas Cumhuriyet Üniversitesi
2006-2011
Ondokuz Mayıs University
2010
Abstract This paper considers some ratio‐type estimators and their properties are studied in stratified random sampling. The results supported by an application with original data.
Abstract In this article, we suggest a new ratio estimator in stratified random sampling based on the Prasad (1989 , B. ( 1989 ). Some improved type estimators of population mean and finite sample surveys . Commun. Statist. Theor. Meth. 18 1 ): 379 – 392 .[Taylor & Francis Online], [Web Science ®] [Google Scholar]) estimator. Theoretically, obtain square error (MSE) for compare it with MSE traditional combined estimate. By comparison, demonstrate that proposed is more efficient than estimate...
A general family of estimators, which use the information two auxiliary variables in stratified random sampling, is proposed to estimate population mean variable under study. Under sampling without replacement scheme, expressions bias and square error (MSE) up first- second-order approximations are derived. The estimators its optimum case discussed. Also, an empirical study carried out show properties estimators.
Gupta and Shabbir 2 Gupta, S. Shabbir, J. 2008. On improvement in estimating the population mean simple random sampling. Appl. Stat., 35(5): 559–566. [Taylor & Francis Online], [Web of Science ®] , [Google Scholar] have suggested an alternative form ratio-type estimators for mean. In this paper, we obtained a corrected version square error (MSE) Gupta–Shabbir estimator, up to first order approximation, optimum case is discussed. We expand estimator stratified sampling propose general classes...
A new calibration estimator is proposed to estimate the population mean in stratified random sampling. The corrected expression of Tracy et al. (2003) calibrated weights are presented and improved introduced. Theoretical variance suggested discussed. Also a simulation study carried out show properties estimator.
This paper suggests a new family of exponential estimators in the two-phase sampling using information an auxiliary attribute. Theoretically, we obtain mean square error (MSE) for these estimators. We compare MSE equations proposed ratio families with literature. As result comparisons, observe that give more efficient results than literature determined conditions obtained theory. In addition, theoretical are supported by application original data sets.
<abstract> In this study, we propose exponential ratio estimators in the stratified two-phase sampling utilizing an auxiliary attribute. The expressions for mean squared error of these exponential-type under two different cases are derived and theoretical comparisons made with competing estimators. We show that proposed have a lower square than simple estimator, usual ratio, product estimators, obtained conditions theory. addition, results supported aid numerical example. </abstract>
We propose a class of estimators for the population mean when there are missing data in set. Obtaining square error equations proposed estimators, we show conditions where more efficient than sample mean, ratio-type and Singh Horn (2000 , S. ( 2000 ). Compromised imputation survey sampling . Metrika 51 : 267 – 276 .[Crossref], [Web Science ®] [Google Scholar]) Deo (2003 B. (2003). Imputation by power transformation. Statist. Pap. 44:555–579.[Crossref], case data. These also supported...
Abstract We propose a new estimator for the population variance using an auxiliary variable in simple random sampling and obtain equations its mean square error (MSE) bias. In addition, theoretically, we show that proposed is more efficient than traditional ratio regression estimators, suggested by Isaki (Citation1983), under certain conditions are defined this article. These satisfied with numerical example. Keywords: Auxiliary informationBiasEfficiencyMean errorRatio estimatorRegression...