On the contraction properties of some high-dimensional quasi-posterior distributions
若干高维拟后验分布的收缩性质
We study the contraction properties of a quasi-posterior distribution $\check{\Pi}_{n,d}$ obtained by combining a quasi-likelihood function and a sparsity inducing prior distribution on $\mathbb{R}^{d}$, as both $n$ (the sample size), and $d$ (the dimension of the parameter) increase. We derive some general results that highlight a set of sufficient conditions under which $\check{\Pi}_{n,d}$ puts increasingly high probability on sparse subsets of $\mathbb{R}^{d}$, and…