Abstract
In this paper, we establish three identities which play a crucial role in deriving the asymptotic distributional risk function and the asymptotic distributional bias of a large class of estimators of a matrix parameter. In particular, we generalize the results in Judge and Bock (The statistical implication of pre-test and Stein-rule estimators in econometrics. North Holland, Amsterdam, 1978). The established results are useful in risk analysis of a class of Stein-rule type matrix estimators.
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Acknowledgments
The author would like to acknowledge the financial support received from Natural Sciences and Engineering Research Council of Canada. Also, the author is thankful to anonymous referees for helpful comments.
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Appendix
Appendix
1.1 Proofs of Theorems 3.1 and 3.2
Proof of Theorem 3.1
Since \(\varvec{\Xi }_{1}^{\frac{1}{2}}\varvec{\Upsilon }\varvec{\Xi }_{1}^{\frac{1}{2}}\) and \(\varvec{\Xi }_{2}^{\frac{1}{2}}\varvec{\Lambda }\varvec{\Xi }_{2}^{\frac{1}{2}}\) are symmetric idempotent matrices, there exist orthogonal matrices \(\varvec{Q}_{1}\) and \(\varvec{Q}_{2}\) such that
Moreover, let \(\varvec{V}=\varvec{Q}_{1}\varvec{\Xi }_{1}^{\frac{1}{2}}\varvec{X} \varvec{\Xi }_{2}^{\frac{1}{2}}\varvec{Q}^{\prime }_{2}\). Then, \(\text{ Vec}\left(\varvec{V}\right)=(\varvec{Q}_{1}\varvec{\Xi }_{1}^{\frac{1}{2}}\otimes \varvec{Q}_{2}\varvec{\Xi }_{2}^{\frac{1}{2}})\text{ Vec}\left(\varvec{X}\right)\) and hence,
with
Therefore, from (5.2), \( \text{ trace}\left(\varvec{\Xi }_{2}\varvec{X}^{\prime }\varvec{\Xi }_{1}\varvec{\Upsilon }\varvec{\Xi }_{1}\varvec{X}\right) =\text{ trace}(\varvec{V}^{\prime }\varvec{Q}_{1}\varvec{\Xi }_{1}^{\frac{1}{2}} \varvec{\Upsilon }\varvec{\Xi }_{1}^{\frac{1}{2}}\varvec{Q}_{1}^{\prime }\varvec{V}) =\varvec{V}_{1}^{\prime }\varvec{V}_{1}.\) Hence, \(\text{ Vec}\left(\text{ E}\left[\phi \left( \text{ trace}\left(\varvec{\Xi }_{2}\varvec{X}^{\prime }\varvec{\Xi }_{1}\varvec{\Upsilon }\varvec{\Xi }_{1}\varvec{X}\right)\right)\varvec{X}\right]\right)= \text{ E}[\phi (\varvec{V}_{1}^{\prime }\varvec{V}_{1}\,) (\varvec{\Xi }_{1}^{-\frac{1}{2}}\varvec{Q}^{\prime }_{1}\otimes \) \( \varvec{\Xi }_{2}^{-\frac{1}{2}}\varvec{Q}^{\prime }_{2})\text{ Vec}(\varvec{V})]\) and then,
Also, from (5.2) and (5.3), \(\text{ E}\left(\varvec{V}_{2}\right)=\varvec{0}\) and \(\text{ Var}\left(\varvec{V}_{2}\right)=\varvec{0}\), so \(\varvec{V}_{2}\) is \(\varvec{0}\) with probability one, and then, \(\text{ E}\left[\phi \left(\varvec{V}_{1}^{\prime }\varvec{V}_{1}\,\right) \varvec{V}_{2}\right]=\varvec{0}\). Further, by using Theorem 1 in Judge and Bock (1978), we get
where \(\varvec{\mu }_{1}\) is given by (5.3). Using (5.1)- (5.3), \(\varvec{\mu }_{1}^{\prime }\varvec{\mu }_{1}=\text{ Vec}\left(\varvec{M}\right)^{\prime } \left(\varvec{\Xi }_{1}\varvec{\Upsilon }\varvec{\Xi }_{1}\otimes \varvec{\Xi }_{2}\right) \text{ Vec}\left(\varvec{M}\right)\), i.e.
Further, combining (5.4) and (5.5), we have
and then, \(\text{ Vec}\left(\! \text{ E}\left[\phi \left( \text{ trace}\left(\varvec{\Xi }_{2}\varvec{X}^{\prime }\varvec{\Xi }_{1}\varvec{\Upsilon }\varvec{\Xi }_{1}\varvec{X}\right)\right)\varvec{X}\right]\right)\!=\! \text{ Vec}\!\left(\!\text{ E}\left(\!\phi \left(\!\chi ^{2}_{pq_{1}\!+\!2}\left(\varvec{\mu }_{1}^{\prime }\varvec{\mu }_{1}\right)\right)\right)\varvec{M}\right)\), this completes the proof. \(\square \)
Proof of Theorem 3.2
From the above computations, we have \(\phi ( \text{ trace}(\varvec{\Xi }_{2}\varvec{X}^{\prime }\varvec{\Xi }_{1} \varvec{\Upsilon }\varvec{\Xi }_{1}\varvec{X})) \,{=}\, \phi (\varvec{V}_{1}^{\prime }\varvec{V}_{1})\). Further, as in Theorem 3.1, we have \(\varvec{V}=\varvec{Q}_{1}\varvec{\Xi }_{1}^{\frac{1}{2}}\varvec{X}\varvec{\Xi }_{2}^{\frac{1}{2}}\varvec{Q}^{\prime }_{2}\) where \(\varvec{Q}_{1}\) and \(\varvec{Q}_{2}\) are the same as in (5.1). We have \(\varvec{X}=\varvec{\Xi }_{1}^{-\frac{1}{2}}\varvec{Q}^{\prime }_{1}\varvec{V}\varvec{Q}_{2} \varvec{\Xi }_{2}^{-\frac{1}{2}}\) and hence,
Therefore, \(\text{ E}\left[\phi \left( \text{ trace}\left(\varvec{\Xi }_{2}\varvec{X}^\prime \varvec{\Xi }_{1}\varvec{\Upsilon }\varvec{\Xi }_{1}\varvec{X}\right)\right) \text{ trace}\left(\varvec{X}^{\prime }\varvec{A}\varvec{X}\right)\right]=\text{ E}[\phi \left(\varvec{V}_{1}^{\prime }\varvec{V}_{1}\,\right)\text{ trace}(\varvec{Q}_{1}\varvec{\Xi }_{1}^{-\frac{1}{2}} \varvec{A}\varvec{\Xi }_{1}^{-\frac{1}{2}}\varvec{Q}^{\prime }_{1}\varvec{V}\varvec{Q}_{2} \varvec{\Xi }_{2}^{-1}\varvec{Q}^{\prime }_{2}\varvec{V}^{\prime })]\). Also, we have \(\text{ trace} (\varvec{Q}_{1}\varvec{\Xi }_{1}^{-\frac{1}{2}} \varvec{A}\varvec{\Xi }_{1}^{-\frac{1}{2}}\varvec{Q}^{\prime }_{1}\varvec{V}\varvec{Q}_{2} \varvec{\Xi }_{2}^{-1}\varvec{Q}^{\prime }_{2}\varvec{V}^{\prime }) =\left(\text{ Vec}\left(\varvec{V}\right)\right)^{\prime } (\varvec{Q}_{1}\varvec{\Xi }_{1}^{-\frac{1}{2}} \varvec{A}\varvec{\Xi }_{1}^{-\frac{1}{2}}\varvec{Q}^{\prime }_{1}\otimes \varvec{Q}_{2}\varvec{\Xi }_{2}^{-1}\varvec{Q}^{\prime }_{2}) \text{ Vec}\left(\varvec{V}\right)\). Further, let
Therefore, \(\left(\text{ Vec}\left(\varvec{V}\right)\right)^{\prime } (\varvec{Q}_{1}\varvec{\Xi }_{1}^{-\frac{1}{2}} \varvec{A}\varvec{\Xi }_{1}^{-\frac{1}{2}}\varvec{Q}^{\prime }_{1}\otimes \varvec{Q}_{2}\varvec{\Xi }_{2}^{-1}\varvec{Q}^{\prime }_{2}) \left(\text{ Vec}\left(\varvec{V}\right)\right) =\varvec{V}_{1}^{\prime }\varvec{G}_{11}\varvec{V}_{1}. \) Further, using Theorem 2 in Judge and Bock (1978), we have
where
this completes the proof. \(\square \)
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Nkurunziza, S. Extension of some important identities in shrinkage-pretest strategies. Metrika 76, 937–947 (2013). https://doi.org/10.1007/s00184-012-0425-5
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DOI: https://doi.org/10.1007/s00184-012-0425-5