Traditional surveys provide estimates that are based only on the sample observations collected for the population characteristic of interest. However, these estimates may have unacceptably large variance for certain domains. Small Area Estimation (SAE) deals with determining precise and accurate estimates for population characteristics of interest for such domains. SAE usually uses least squares or maximum likelihood procedures incorporating prior information and current survey data. Many available methods in SAE use constraints in equality form. However there are practical situations where certain inequality restrictions on model parameters are more realistic. It will lead to Inequality Constrained Least Squares (ICLS) estimates if the method used is least squares. In this study ICLS estimation procedure is applied to many proposed small area estimates.
机构:
Northeast Normal Univ, Sch Math & Stat, Changchun 130024, Peoples R ChinaNortheast Normal Univ, Sch Math & Stat, Changchun 130024, Peoples R China
Diao, Huai-An
Wei, Yimin
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机构:
Fudan Univ, Sch Math Sci, Shanghai 200433, Peoples R China
Fudan Univ, Shanghai Key Lab Contemporary Appl Math, Shanghai 200433, Peoples R ChinaNortheast Normal Univ, Sch Math & Stat, Changchun 130024, Peoples R China
Wei, Yimin
Xie, Pengpeng
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机构:
Ocean Univ China, Sch Math Sci, Qingdao 266100, Peoples R ChinaNortheast Normal Univ, Sch Math & Stat, Changchun 130024, Peoples R China
机构:
Faculty of Geomatics,East China Institute of Technology
Jiangxi Province Key Lab for DigitalFaculty of Geomatics,East China Institute of Technology
机构:
East China Inst Technol, Fac Geomat, Nanchang 330013, Jiangxi, Peoples R China
Jiangxi Prov Key Lab Digital Land, Fuzhou 344000, Fujian, Peoples R ChinaEast China Inst Technol, Fac Geomat, Nanchang 330013, Jiangxi, Peoples R China