On estimation of variance components with constraints |
| |
| Affiliation: | 1. Geosciences and Geohazard Department, Indian Institute of Remote Sensing, 4 Kalidas Road, Dehradun, 248001, India;2. Department of Applied Geology, Indian Institute of Technology (Indian School of Mines), Dhanbad, India;1. Qingdao University, 308 Ningxia Road, Qingdao 266071, China;2. V. N. Karazin Kharkiv National University, 4 Svobody Sq., Kharkiv 61022, Ukraine;3. Harbin Engineering University, 145 Nantong Street, Nangang District, Harbin 15,0001, China;1. Institute of Solar-Terrestrial Physics of Siberian Branch of Russian Academy of Sciences, Russia;2. Irkutsk State University, Russia;3. Lomonosov Moscow State University, Russia;1. Department of Physics, Quaid-i-Azam University, Islamabad 45320, Pakistan;2. Sorbonne Université, Ecole polytechnique, Institut Polytechnique de Paris, Université Paris Saclay, Observatoire de Paris, CNRS, Laboratoire de Physique des Plasmas (LPP), 75005 Paris, France;3. The Abdus Salam International Centre of Theoretical Physics, Trieste, Italy;4. Cardiff School of Education & Social Policy, Cardiff Metropolitan University, Cyncoed Campus, Cardiff, UK;1. Sharjah Academy for Astronomy, Space Sciences and Technology, University of Sharjah, University City, Sharjah, United Arab Emirates;2. Department of Applied Physics and Astronomy, University of Sharjah, University City, Sharjah, United Arab Emirates;1. Institute of Solar-Terrestrial Physics SB RAS, 126a Lermontov st., Irkutsk 664033, Russia;2. Institute of the Earth''s Crust SB RAS, 128 Lermontova St., Irkutsk 664033, Russia;3. Geological institute SB RAS, 6a Sakhyanovoy str., Ulan-Ude 670047, Russia;4. Far Eastern Federal University, 10 Ajax Bay, Russky Island, Vladivostok 690922, Russia;5. Institute of Applied Mathematics FEB RAS, 7 Radio str., Vladivostok 690041, Russia;6. Institute of Earthquake Forecasting, China Earthquake Administration, 63 Fuxing Road, Haidian District, Beijing 100036, China |
| |
| Abstract: | The so-called linear approach to estimating linear functions of variance and/or covariance components clearly shows the well-known connection between quadratic, invariant and unbiased, estimation and the classical linear theory methods, LSE and BLUE. This approach allows us to consider and to use further results of the linear theory for variance-covariance components estimation.In the present paper the minimax invariant quadratic estimators of linear functions of variance-covariance components under full or partial restrictions on the parameter set are investigated. |
| |
| Keywords: | |
| 本文献已被 ScienceDirect 等数据库收录！ |
|
