The Penalized Profile Sampler.
The Penalized Profile Sampler.
复制标题
DOI：
10.1016/j.jmva.2008.05.001
复制
发表时间：
2009-03-01
影响因子：
1.6
通讯作者：
Kosorok MR
中科院分区：
文献类型：
--
作者：
Cheng G;Kosorok MR
The penalized profile sampler for semiparametric inference is an extension of the profile sampler method obtained by profiling a penalized log-likelihood. The idea is to base inference on the posterior distribution obtained by multiplying a profiled penalized log-likelihood by a prior for the parametric component, where the profiling and penalization are applied to the nuisance parameter. Because the prior is not applied to the full likelihood, the method is not strictly Bayesian. A benefit of this approximately Bayesian method is that it circumvents the need to put a prior on the possibly infinite-dimensional nuisance components of the model. We investigate the first and second order frequentist performance of the penalized profile sampler, and demonstrate that the accuracy of the procedure can be adjusted by the size of the assigned smoothing parameter. The theoretical validity of the procedure is illustrated for two examples: a partly linear model with normal error for current status data and a semiparametric logistic regression model. Simulation studies are used to verify the theoretical results.
登录
查看更多内容
影响因子：
1.6
作者：
Murphy, SA;van der Vaart, AW
通讯作者：
van der Vaart, AW
影响因子：
2.7
作者：
GOOD, IJ;GASKINS, RA
通讯作者：
GASKINS, RA
DOI：
10.1198/016214504000001772
发表时间：
2005-09-01
影响因子：
3.7
作者：
Lee, BL;Kosorok, MR;Fine, JP
通讯作者：
Fine, JP
影响因子：
4.5
作者：
Ma, SG;Kosorok, MR
通讯作者：
Kosorok, MR
影响因子：
1.6
作者：
Ma, SG;Kosorok, MR
通讯作者：
Kosorok, MR