PAC-Bayesian estimation and prediction in sparse additive models

作者：Guedj Benjamin^*; Alquier Pierre

来源：Electronic Journal of Statistics, 2013, 7(0): 264-291.

DOI：10.1214/13-EJS771

• Additive models
• sparsity
• regression estimation
• PAC-Bayesian bounds
• oracle inequality
• MCMC
• stochastic search

The present paper is about estimation and prediction in high-dimensional additive models under a sparsity assumption (p %26gt;%26gt; n paradigm). A PAC-Bayesian strategy is investigated, delivering oracle inequalities in probability. The implementation is performed through recent outcomes in high-dimensional MCMC algorithms, and the performance of our method is assessed on simulated data.

• 出版日期2013