An important task in building regression models is to decide which regressors should be included in the final model. In a Bayesian approach, variable selection can be performed using mixture priors with a spike and a slab component for the effects subject to selection. As the spike is concentrated at zero, variable selection is based on the probability of assigning the corresponding regression effect to the slab component. These posterior inclusion probabilities can be determined by MCMC sampling. In this paper we compare the MCMC implementations for several spike and slab priors with regard to posterior inclusion probabilities and their sampling efficiency for simulated data. Further, we investigate posterior inclusion probabilities analytically for different slabs in two simple settings. Application of variable selection with spike and slab priors is illustrated on a data set of psychiatric patients where the goal is to identify covariates affecting metabolism.

Gertraud Malsiner-Walli

Helga Wagner

Austrian Journal of Statistics

The Austrian Journal of Statistics is an open-access journal (without any fees) with a long history and is published approximately quarterly by the Austrian Statistical Society. Its general objective is to promote and extend the use of statistical methods in all kind of theoretical and applied disciplines.     The Austrian Journal of Statistics is indexed in many data bases, such as Scopus (by Elsevier), Web of Science - ESCI by Clarivate Analytics (formely Thompson & Reuters), DOAJ, Scimago, and many more. The current estimated impact factor (via Publish or Perish) is 0.775, see HERE, or even more indices HERE. Austrian Journal of Statistics ISNN number is 1026597X    Original papers and review articles in English will be published in the Austrian Journal of Statistics if judged consistently with these general aims. All papers will be refereed. Special topics sections will appear from time to time. Each section will have as a theme a specialized area of statistical application, theory, or methodology. Technical notes or problems for considerations under Shorter Communications are also invited. A special section is reserved for book reviews.

The Austrian Journal of Statistics is an open-access journal (with no fees) that has a long history and is published approximately quarterly by the Austrian Statistical Society. Its main objective is to promote and extend the use of statistical methods across various theoretical and applied disciplines. The Austrian Journal of Statistics is indexed in numerous databases, including Scopus (by Elsevier), Web of Science - ESCI by Clarivate Analytics (formerly Thomson & Reuters), DOAJ, Scimago, and many more. The current estimated impact factor (via Publish or Perish) is 0.775; further details can be found here. The ISNN number for the journal is 1026597X. Original papers and review articles in English that align with these general aims will be published in the Austrian Journal of Statistics, and all submissions will undergo peer review. Special topic sections will appear from time to time, each focusing on a specific area of statistical application, theory, or methodology. Technical notes or problems for consideration under Shorter Communications are also invited. A special section is reserved for book reviews.

《Austrian Journal of Statistics》是一本开放获取的期刊（无任何费用），由奥地利统计学会出版，历史悠久，约每季度出版一次。其主要目标是促进和扩展统计方法在各种理论和应用学科中的使用。《Austrian Journal of Statistics》被多个数据库收录，如Elsevier的Scopus、Clarivate Analytics（前身为汤森路透）的Web of Science - ESCI、DOAJ、Scimago等。目前估计的影响因子为0.775（通过Publish or Perish计算），具体信息请见此处。该期刊的ISNN号为1026597X。符合上述一般目标的英文原创论文和综述文章将被《Austrian Journal of Statistics》接受并发表。所有论文均需经过同行评审。期刊不定期会发布专题部分，每个部分将围绕统计应用、理论或方法论的特定领域展开。也欢迎提交技术笔记或短篇通讯中的问题。期刊特别设有书评专栏。

Comparing Spike and Slab Priors for Bayesian Variable Selection

This paper compares the MCMC implementations for several spike and slab priors with regard to posterior inclusion probabilities and their sampling efficiency for simulated data and investigates posterior inclusion probability analytically for different slabs in two simple settings.

Comparing Spike and Slab Priors for Bayesian Variable Selection

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Journal Info

Category	Quartile
STATISTICS & PROBABILITY	4