• 제목/요약/키워드: Statistical efficiency

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Nonparametric Selection Procedures and Their Efficiency Comparisons

  • Sohn, Joong-K.;Shanti S.Gupta;Kim, Heon-Joo
    • Communications for Statistical Applications and Methods
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    • 제1권1호
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    • pp.41-51
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    • 1994
  • We consider nonparametric procedures for the selection and ranking problems. Tukey's generalized lambda distribution is condidered as the distribution for the score function because the distribution can approximate many well-known contionuous distributions. Also we compare these procedures in terms of efficiency, defined by the ratio of a probability of a correct selection divided by the expected selected subset size.

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One-step Least Squares Fitting of Variogram

  • Choi, Hye-Mi
    • Communications for Statistical Applications and Methods
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    • 제12권2호
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    • pp.539-544
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    • 2005
  • In this paper, we propose the one-step least squares method based on the squared differences to estimate the parameters of the variogram used for spatial data modelling, and discuss its asymptotic efficiency. The proposed method does not require to specify lags of interest and partition lags, so that we can delete the subjectiveness and ambiguity originated from the lag selection in estimating spatial dependence.

NONLINEAR ASYMMETRIC LEAST SQUARES ESTIMATORS

  • Park, Seung-Hoe;Kim, Hae-Kyung;Lee, Young
    • Journal of the Korean Statistical Society
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    • 제32권1호
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    • pp.47-64
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    • 2003
  • In this paper, we consider the asymptotic properties of asymmetric least squares estimators for nonlinear regression models. This paper provides sufficient conditions for strong consistency and asymptotic normality of the proposed estimators and derives asymptotic relative efficiency of the pro-posed estimators to the regression quantile estimators. We give some examples and results of a Monte Carlo simulation to compare the asymmetric least squares estimators with the regression quantile estimators.

Minimax Choice and Convex Combinations of Generalized Pickands Estimator of the Extreme Value Index

  • Yun, Seokhoon
    • Journal of the Korean Statistical Society
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    • 제31권3호
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    • pp.315-328
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    • 2002
  • As an extension of the well-known Pickands (1975) estimate. for the extreme value index, Yun (2002) introduced a generalized Pickands estimator. This paper searches for a minimax estimator in the sense of minimizing the maximum asymptotic relative efficiency of the Pickands estimator with respect to the generalized one. To reduce the asymptotic variance of the resulting estimator, convex combinations of the minimax estimator are also considered and their asymptotic normality is established. Finally, the optimal combination is determined and proves to be superior to the generalized Pickands estimator.

Minimum Disparity Estimation for Normal Models: Small Sample Efficiency

  • Cho M. J.;Hong C. S.;Jeong D. B.
    • Communications for Statistical Applications and Methods
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    • 제12권1호
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    • pp.149-167
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    • 2005
  • The minimum disparity estimators introduced by Lindsay and Basu (1994) are studied empirically. An extensive simulation in this paper provides a location estimate of the small sample and supplies empirical evidence of the estimator performance for the univariate contaminated normal model. Empirical results show that the minimum generalized negative exponential disparity estimator (MGNEDE) obtains high efficiency for small sample sizes and dominates the maximum likelihood estimator (MLE) and the minimum blended weight Hellinger distance estimator (MBWHDE) with respect to efficiency at the contaminated model.

On Nonparametric Estimation of Data Edges

  • Park, Byeong U.
    • Journal of the Korean Statistical Society
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    • 제30권2호
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    • pp.265-280
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    • 2001
  • Estimation of the edge of a distribution has many important applications. It is related to classification, cluster analysis, neural network, and statistical image recovering. The problem also arises in measuring production efficiency in economic systems. Three most promising nonparametric estimators in the existing literature are introduced. Their statistical properties are provided, some of which are new. Themes of future study are also discussed.

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스마트팜 도입 딸기농가의 생산효율성 통계분석 (Statistical analysis of Production Efficiency on the Strawberry Farms Using Smart Farming)

  • 최돈우;임청룡
    • 품질경영학회지
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    • 제46권3호
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    • pp.707-716
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    • 2018
  • Purpose: This study aims to analyze the management performance and production efficiency of strawberry farmers who introduced smart farming, one of the primary symbols of the fourth industrial revolution in the agricultural sector. Methods: We conducted an empirical survey of strawberry farms using smart farming and analyzed production efficiency using DEA method. Results: First, difficulties for strawberry farmers introducing smart farming included time and money spent on parts replacement and additional costs due to compatibility problems with existing facilities after the adoption. Second, strawberry farmers using smart farming increased their total income by producing higher yield and improving quality thanks to the competent growth management. Third, the analysis of production efficiencies before and after smart farming found improvement in technical efficiency, pure technical efficiency, and scale efficiency. But, the gaps in technical and scale efficiencies among the farms widened. Conclusion: Based on the results above, following policy suggestions are offered. First, an environment control technology suitable for strawberry farming needs to be developed. Second, the smart farming technology needs to be standardized by the government. Third, new smart farm models need to be developed to accommodate to the facilities and environment in Korea through collecting big data including high-quality data on the environment, growth, and yield. Fourth, continuing education needs to be provided to narrow the gap in smart farming technology among strawberry farmers.

Efficiency Evaluation of Financial Support for Rural Industry Revitalization in Eastern China

  • Zhou, Lin-lin;Sim, Jae-yeon
    • International journal of advanced smart convergence
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    • 제11권1호
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    • pp.101-110
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    • 2022
  • The purpose of this study is to evaluate the efficiency of financial support for rural industry revitalization in eastern China. Comparative analysis of the efficiency of provincial financial support for rural industrial revitalization in eastern China can provide reference for various provinces to formulate financial policies for rural revitalization. In the research process, 5 evaluation indicators were selected using the panel data of the 2016-2021 "China Financial Statistical Yearbook" and "China Statistical Yearbook", and the DEA and Malmquist index methods were used for calculation. The results show that the average efficiency of financial support for rural revitalization in the 10 eastern provinces from 2015 to 2020 was generally higher, with the efficiency values all higher than 0.8, and reached 0.908 in 2017. The comprehensive efficiency of financial support for rural industry revitalization in Tianjin, Shanghai and Hainan has reached the best. From 2015 to 2020, the total factor productivity of financial support for rural industry revitalization in the eastern region has a "V"-shaped fluctuation. Total factor productivity has the fastest growth. The provinces are Beijing, Hebei and Shandong showing negative growth. It is recommended that relevant provinces improve their strategies for financial support for the revitalization of rural industries. The scope of future research should be expanded to most areas of China and the evaluation indicators should be optimized.

Statistical Estimation of Optimal Portfolios for non-Gaussian Dependent Returns of Assets

  • Taniguchi, Masanobu;Shiraishi, Hiroshi
    • 한국통계학회:학술대회논문집
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    • 한국통계학회 2005년도 추계 학술발표회 논문집
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    • pp.55-58
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    • 2005
  • This paper discusses the asymptotic efficiency of estimators for optimal portfolios when returns are vector-valued non-Gaussian stationary processes. We give the asymptotic distribution of portfolio estimators ${\hat{g}}$ for non-Gaussian dependent return processes. Next we address the problem of asymptotic efficiency for the class of estimators ${\hat{g}}$ First, it is shown that there are some cases when the asymptotic variance of ${\hat{g}}$ under non-Gaussianity can be smaller than that under Gaussianity. The result shows that non-Gaussianity of X(t) does not always affect worse. Second, we give a necessary and sufficient condition for ${\hat{g}}$ to be asymptotically efficient when the return process is Gaussian, which shows that ${\hat{g}}$ is not asymptotically efficient generally. From this point of view we propose to use maximum likelihood type estimators for g, which are asymptotically efficient. We examine our approach numerically.

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On inference of multivariate means under ranked set sampling

  • Rochani, Haresh;Linder, Daniel F.;Samawi, Hani;Panchal, Viral
    • Communications for Statistical Applications and Methods
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    • 제25권1호
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    • pp.1-13
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    • 2018
  • In many studies, a researcher attempts to describe a population where units are measured for multiple outcomes, or responses. In this paper, we present an efficient procedure based on ranked set sampling to estimate and perform hypothesis testing on a multivariate mean. The method is based on ranking on an auxiliary covariate, which is assumed to be correlated with the multivariate response, in order to improve the efficiency of the estimation. We showed that the proposed estimators developed under this sampling scheme are unbiased, have smaller variance in the multivariate sense, and are asymptotically Gaussian. We also demonstrated that the efficiency of multivariate regression estimator can be improved by using Ranked set sampling. A bootstrap routine is developed in the statistical software R to perform inference when the sample size is small. We use a simulation study to investigate the performance of the method under known conditions and apply the method to the biomarker data collected in China Health and Nutrition Survey (CHNS 2009) data.