An empirical Bayes derivation of best linear unbiased predictors
Let (Y1,θ1),…,(Yn,θn) be independent real-valued random vectors with Yi, given θi, is distributed according to a distribution depending only on θi for i=1,…,n. In this paper, best linear unbiased predictors (BLUPs) of the θi's are investigated. We show that BLUPs of θi's do not exist in ce...
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| Format: | Article |
| Language: | English |
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Wiley
2002-01-01
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| Series: | International Journal of Mathematics and Mathematical Sciences |
| Online Access: | http://dx.doi.org/10.1155/S016117120211009X |
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| _version_ | 1849401544671232000 |
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| author | Rohana J. Karunamuni |
| author_facet | Rohana J. Karunamuni |
| author_sort | Rohana J. Karunamuni |
| collection | DOAJ |
| description | Let (Y1,θ1),…,(Yn,θn) be independent real-valued random vectors with Yi, given θi, is distributed according to a distribution depending only on θi for i=1,…,n. In this paper, best linear unbiased predictors (BLUPs) of the θi's are investigated. We show that BLUPs of θi's do not exist in certain situations. Furthermore, we present a general empirical Bayes technique for deriving BLUPs. |
| format | Article |
| id | doaj-art-8cf1e34d75c543e995cb51e3df73b58c |
| institution | Kabale University |
| issn | 0161-1712 1687-0425 |
| language | English |
| publishDate | 2002-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | International Journal of Mathematics and Mathematical Sciences |
| spelling | doaj-art-8cf1e34d75c543e995cb51e3df73b58c2025-08-20T03:37:44ZengWileyInternational Journal of Mathematics and Mathematical Sciences0161-17121687-04252002-01-01311270371410.1155/S016117120211009XAn empirical Bayes derivation of best linear unbiased predictorsRohana J. Karunamuni0Department of Mathematical and Statistical Sciences, University of Alberta, Alberta, Edmonton T6G 2G1, CanadaLet (Y1,θ1),…,(Yn,θn) be independent real-valued random vectors with Yi, given θi, is distributed according to a distribution depending only on θi for i=1,…,n. In this paper, best linear unbiased predictors (BLUPs) of the θi's are investigated. We show that BLUPs of θi's do not exist in certain situations. Furthermore, we present a general empirical Bayes technique for deriving BLUPs.http://dx.doi.org/10.1155/S016117120211009X |
| spellingShingle | Rohana J. Karunamuni An empirical Bayes derivation of best linear unbiased predictors International Journal of Mathematics and Mathematical Sciences |
| title | An empirical Bayes derivation of best linear unbiased predictors |
| title_full | An empirical Bayes derivation of best linear unbiased predictors |
| title_fullStr | An empirical Bayes derivation of best linear unbiased predictors |
| title_full_unstemmed | An empirical Bayes derivation of best linear unbiased predictors |
| title_short | An empirical Bayes derivation of best linear unbiased predictors |
| title_sort | empirical bayes derivation of best linear unbiased predictors |
| url | http://dx.doi.org/10.1155/S016117120211009X |
| work_keys_str_mv | AT rohanajkarunamuni anempiricalbayesderivationofbestlinearunbiasedpredictors AT rohanajkarunamuni empiricalbayesderivationofbestlinearunbiasedpredictors |