We propose a quasi-Bayesian method to conduct inference for the production frontier. This approach combines multiple first-stage extreme quantile estimates by the quasi-Bayesian method to produce the point estimate and confidence interval for the production frontier. We show the asymptotic properties of the proposed estimator and the validity of the inference procedure. The finite sample performance of our method is illustrated through simulations and an empirical application.
AbstractThe Maiji Grottoes a famous grotto group located on the ancient “Silk Road”. It occupies a significant place in the history of grottoes and has also contributed to the communication of Buddhist art. Since the 1970s, the Chinese government and restoration professionals have made many efforts to restore the Maiji Grottoes for purposes of both scientific research and cultural protection. However, some severe diseases have repeatedly broken out in several grottoes, which require urgent treatment. In this paper, 21 grottoes and about 137.72 m2 of murals from 21 grottoes reinforced by PVAc emulsion were investigated. The results indicated the most common diseases are cracking, hollowing, discoloration, mildew, saline-alkaline and flaking. These diseases have a close relationship with the microenvironment of each grotto. Moreover, the LC analysis showed the PVAc look like remained practically the same reinforce effect, regardless of changes in time and climate. Thus, the PVAc could be used in the protection of murals for which a controlled environment should be provided to prevent these renewed diseases.
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