Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Bayesian frequentist hybrid inference   Bayesian and frequentist methods differ in many aspects, but share some basic
optimality properties. In practice, there are situations in which one of the
methods is more preferred by some criteria. We consider the case of inference
about a set of multiple parameters, which can be divided into two disjoint
subsets. On one set, a frequentist method may be favored and on the other, the
Bayesian. This motivates a joint estimation procedure in which some of the
parameters are estimated Bayesian, and the rest by the maximum-likelihood
estimator in the same parametric model, and thus keep the strengths of both the
methods and avoid their weaknesses. Such a hybrid procedure gives us more
flexibility in achieving overall inference advantages. We study the consistency
and high-order asymptotic behavior of the proposed estimator, and illustrate
its application. Also, the results imply a new method for constructing
objective prior.

7
The categories of this paper are: hep-th
23
The categories of this paper are: solv-int
6
The categories of this paper are: astro-ph
10
The categories of this paper are: q-bio
37
The categories of this paper are: supr-con
27
The categories of this paper are: comp-gas
9
The categories of this paper are: nlin
21
The categories of this paper are: adap-org
0
The categories of this paper are: hep-ph
33
The categories of this paper are: plasm-ph
13
The categories of this paper are: quant-ph
19
The categories of this paper are: eess
31
The categories of this paper are: ao-sci
26
The categories of this paper are: bayes-an
34
The categories of this paper are: chem-ph
5
The categories of this paper are: gr-qc