A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2017; you can also visit the original URL.
The file type is
Inference about a parameter of interest in presence of a nuisance parameter can be based on an integrated likelihood function. We analyze the behaviour of inferential quantities based on such a pseudolikelihood in a two-index asymptotics framework, in which both sample size and dimension of the nuisance parameter may diverge to infinity. We show that the integrated likelihood, if chosen wisely, largely outperforms standard likelihood methods, such as the profile likelihood. These results aredoi:10.1214/15-ejs1045 fatcat:cq5hhaxp5ve7lpywx5afpdd5a4