efficient estimator
An Efficient Estimator Improving the Searls’ Normal Mean Estimator for Known Coefficient of Variation
... (Efficient) Estimator Of Normal Mean (PPDUEFFESTROMEAN)” of the normal population mean lies in trying to know it through an illustrative “Simulation Empirical Numerical Study”, as is attempted in this ...
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MoL 2004 02: A Consistent and Efficient Estimator for the Data Oriented Parsing Model
... and efficient estimator for the Data- Oriented Parsing ...The estimator has a clear theoretical motivation in a generalization of the maximum-likelihood principle to held-out ...our estimator ...
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Efficient Estimator for Population Variance Using Auxiliary Variable
... type estimator. An efficient estimator of population variance using coefficient of correlation and the inter quartile range of the auxiliary variable has been ...proposed estimator have been ...
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Further Increasing Fisher's Information for Parameters of Association in Accelerated Failure Time Models via Double Extreme Ranks
... Double Extreme Ranked Set Sampling (DERSS) was first introduced by Samawi (2002) as a modification to the well-known Ranked Set Sampling (RSS) and Extreme Ranked Set Sampling (ERSS). In this article, we provide a ...
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More Efficient Estimation for Logistic Regression with Optimal Subsamples
... new estimator has a higher estimation ...more efficient estimator if the sampling ratio, the ratio of the subsample size to the full data sample size, does not converge to ...the estimator ...
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Improved Exponential Type Estimators for Finite Population Mean in Stratified Random Sampling
... In sampling theory the role of auxiliary information has a great importance. It is well known that using suitable auxiliary information such as population total, mean, skewness, correlation, attribute etc. can improve ...
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An Ecient Class of Estimators of Population Mean in Two-Phase Sampling Using Two Auxiliary Variables
... an efficient estimator for population mean in two-phase sampling using two auxiliary variables following Vishwakarma and Kumar ...proposed estimator is compared with some competitor estimators both ...
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Almost Efficient Estimation of Relative Risk Regression
... regression estimator and develop an alternative, almost efficient estimator for the RR regression ...almost efficient estimator while avoiding convergence ...
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Mixture Ratio Estimators Using Multi Auxiliary Variables and Attributes for Two Phase Sampling
... ratio estimator under full information case is recommended for estimating the finite pop- ulation mean since it is the most efficient estimator compared to mean per unit, ratio estimator using ...
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PubMedCentral-PMC4715780.pdf
... more efficient estimator by making full use of available covariate information for the additive hazards model with data from a stratified case-cohort design with rare (the traditional situation) and ...
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Mixture Regression Estimators Using Multi Auxiliary Variables and Attributes in Two Phase Sampling
... [3]; it is preferred when the study variable is highly positively correlated with the auxiliary variable. Watson [4] used the regression estimator of leaf area on leaf weight to estimate the average area of the ...
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Performance of Existing Biased Estimators and the Respective Predictors in a Misspecified Linear Regression Model
... class estimator and r-k class estimator over some existing esti- mators, ...Regression Estimator (MRE) under misspecified regres- sion model due to excluding relevant variable with correctly ...
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Ready Queue Mean Time Estimation in Lottery Scheduling using Auxiliary Variables in Multiprocessor Environment
... From above analysis it is clear that auxiliary variables play important role in the prediction of remaining processing time of ready queue. The length of confidence interval gets reduced if the auxiliary variables are ...
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Extreme M quantiles as risk measures: from L1 to Lp optimization
... then pick out a suitable k corresponding to the first stable part of the plot [see, e.g., Sec- tion 3 in de Haan and Ferreira (2006)]. A vexing defect with this heuristic approach from a forecasting perspective is that ...
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Estimators of Linear Regression Model and Prediction under Some Assumptions Violation
... OLS estimator is inefficient even though ...the estimator provided by Cochrane and Orcutt [17], Paris and Winstern [18], Hildreth and Lu [19], Durbin [20], Theil [21], the Maximum Likelihood and the Maximum ...
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On comparison some estimators in small area study
... Stein estimator over direct estimator, we also include some more competitor ...synthetic estimator using the previous year’s batting average, two composite estimators that we mentioned, the Bayes ...
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Adjustment of the Auxiliary Variable(s) for Estimation of a Finite Population Mean
... weighted estimator of the population mean. The proposed estimator is compared with the estimators proposed by Chakrabarty (1979), Singh and Singh (1997), Singh (2002) and Singh et ...
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A COMPARISON OF NONPARAMETRIC ESTIMATORS FOR LENGTH DISTRIBUTION IN LINE SEGMENT PROCESSES
... likelihood estimator (NPMLE) is based on the assumption of Poisson ...this estimator is quite robust and preserves its superior behaviour also if the underlying point process is not Poisson and if the ...
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The Zig Zag process and super efficient sampling for Bayesian analysis of big data
... unbiased estimator, then the Zig-Zag process can be super-efficient: after an initial preprocessing step, essentially independent samples from the posterior distribution are obtained at a computational cost ...
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Empirical likelihood based inference in Poisson autoregressive model with conditional moment restrictions
... the estimator (denoted by ALS) given by ...squares estimator (LS), the weighted least squares estima- tor (WLS), and the maximum likelihood estimation (MLE), we compute the mean square errors based on the ...
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