von Rosen, Tatjana and Von Rosen, Dietrich and Volaufova, Julia
(2020).
A new method for obtaining explicit estimators in unbalanced mixed linear models.
Statistical Papers. 61
, 371-383
[Journal article]
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Available under License Creative Commons Attribution. 684kB |
Abstract
The general unbalanced mixed linear model with two variance components is considered. Through resampling it is demonstrated how the fixed effects can be estimated explicitly. It is shown that the obtained nonlinear estimator is unbiased and its variance is also derived. A condition is given when the proposed estimator is recommended instead of the ordinary least squares estimator.
Authors/Creators: | von Rosen, Tatjana and Von Rosen, Dietrich and Volaufova, Julia | ||||||
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Title: | A new method for obtaining explicit estimators in unbalanced mixed linear models | ||||||
Series Name/Journal: | Statistical Papers | ||||||
Year of publishing : | 2020 | ||||||
Volume: | 61 | ||||||
Page range: | 371-383 | ||||||
Number of Pages: | 13 | ||||||
Publisher: | Springer | ||||||
ISSN: | 0932-5026 | ||||||
Language: | English | ||||||
Publication Type: | Journal article | ||||||
Article category: | Scientific peer reviewed | ||||||
Version: | Published version | ||||||
Copyright: | Creative Commons: Attribution 4.0 | ||||||
Full Text Status: | Public | ||||||
Subjects: | (A) Swedish standard research categories 2011 > 1 Natural sciences > 101 Mathematics > 10106 Probability Theory and Statistics | ||||||
Keywords: | Linear mixed models, Explicit estimators, Ordinary least squares estimators, Maximum likelihood estimators, Abstract bootstrapping | ||||||
URN:NBN: | urn:nbn:se:slu:epsilon-p-105239 | ||||||
Permanent URL: | http://urn.kb.se/resolve?urn=urn:nbn:se:slu:epsilon-p-105239 | ||||||
Additional ID: |
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ID Code: | 16917 | ||||||
Faculty: | NJ - Fakulteten för naturresurser och jordbruksvetenskap | ||||||
Department: | (NL, NJ) > Dept. of Energy and Technology | ||||||
Deposited By: | SLUpub Connector | ||||||
Deposited On: | 15 May 2020 11:49 | ||||||
Metadata Last Modified: | 15 Jan 2021 19:47 |
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