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Using a simulation analysis to evaluate the impact of crop mapping error on crop area estimation from stratified sampling

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International Journal of Digital Earth 2019年第9期12卷 1046-1066页

作者： Peijun Sun Russell G.Congalton Yaozhong Pan State Key Laboratory of Remote Sensing Science Jointly Sponsored by Beijing Normal University and Institute of Remote Sensing and Digital Earth of Chinese Academy of SciencesBeijingPeople’s Republic of China Institute of Remote Sensing and Engineering Faculty of Geographical ScienceBeijing Normal UniversityBeijingPeople’s Republic of China Department of Natural Resources&the Environment University of New HampshireDurhamNHUSA

To analyze the efficiency of area estimations(*** accuracy and variation of estimation)impacted by crop mapping error,we simulated error at eight levels for thematic maps using a stratified sampling estimation *** results show that the estimation efficiency is influenced by the combination of the sample size and the error *** the trade-offs between sample size and error level showed that reducing the crop mapping error level provides the most benefit(*** estimation efficiency).Further,sampling performance differed based on the heterogeneity of the crop *** results demonstrated that the influence of increasing the error level on estimation efficiency is more detrimental in heterogeneous areas than in homogeneous ***,to obtain higher estimation efficiency,a larger sample size and lower error level or both are needed,especially in heterogeneous *** suggest that existing land-cover maps should first be used to determine the heterogeneity of the *** appropriate sample size for these areas then can be determined according to all three factors:heterogeneity,expected estimation efficiency,and sampling ***,extending our understanding of the impacts of crop mapping error is necessary for decision making to improve our ability to effectively estimate crop area.

关键词： Crop mapping error area estimation estimation efficiency landscape heterogeneity stratified sampling

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Composite Quantile estimation for Kink Model with Longitudinal Data

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Acta Mathematica Sinica,English Series 2023年第3期39卷 412-438页

作者： Chuang WAN Wei ZHONG Ying FANG School of Statistics and Data Science Nankai UniversityTianjin 300071P.R.China MOE Key Lab of Econometrics WISEDepartment of Statistics and Data ScienceSchool of EconomicsXiamen UniversityXiamen 361000P.R.China

Kink model is developed to analyze the data where the regression function is two-stage piecewise linear with respect to the threshold covariate but continuous at an unknown kink *** quantile regression for longitudinal data,kink point where the kink effect happens is often assumed to be heterogeneous across different ***,the kink point tends to be the same across different quantiles,especially in a region of neighboring quantile *** such homogeneity information could increase the estimation efficiency of the common kink *** this paper,we propose a composite quantile estimation approach for the common kink point by combining information from multiple neighboring *** normality of the proposed estimator is *** addition,we also develop a sup-likelihood-ratio test to check the existence of the kink effect at a given quantile level.A test-inversion confidence interval for the common kink point is also developed based on the quantile rank score *** simulation studies show that the proposed composite kink estimator is more efficient than the single quantile regression *** also illustrate the proposed method via an application to a longitudinal data set on blood pressure and body mass index.

关键词： Asymptotical normality composite quantile estimation estimation efficiency kink design model longitudinal data

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