@article{16854701518b41debb6ddd11782fc2f7,

title = "Optimal estimator under risk matrix in a seemingly unrelated regression model and its generalized least squares expression",

abstract = "A set of multiple regression models whose error terms have possibly contemporaneous correlations is called a seemingly unrelated regression model. In this paper, a best equivariant estimator of the regression vector under risk matrix is established in a seemingly unrelated regression model. It should be noted that an estimator optimal with respect to risk matrix remains optimal under a broad range of quadratic loss functions. A generalized least squares expression of our estimator is also presented.",

keywords = "Elliptically symmetric distribution, Equivariant estimator, Generalized least squares, Risk matrix, Seemingly unrelated regression model",

author = "Shun Matsuura and Hiroshi Kurata",

note = "Funding Information: The authors would like to thank anonymous reviewers for many constructive and useful comments. Matsuura{\textquoteright}s portion of this work is supported by JSPS KAKENHI Grant Number 20K11713. Kurata{\textquoteright}s portion of this work is supported by JSPS KAKENHI Grant Number 19K11853. Publisher Copyright: {\textcopyright} 2021, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.",

year = "2021",

doi = "10.1007/s00362-021-01232-5",

language = "English",

journal = "Statistical Papers",

issn = "0932-5026",

publisher = "Springer New York",

}