Risk Analysis Research Center Seminar

July 11(Tue), 2017 13:30-15:00

Admission Free,No Booking Necessary

The Institute of Statistical Mathematics, Tokyo, Japan.
Seminar room5 (3F)
Prof. Song Xi Chen (Peking University)
Detecting Rare and Faint Signals via Thresholding Maximum Likelihood Estimators
Motivated by the analysis of RNA sequencing (RNA-seq) data for genes differentially expressed across multiple conditions, we consider detecting rare and faint signals response variables. in high-dimensional response variables. We address the signal detection problem under a general framework, which includes generalized linear models for count-valued responses as special cases. We propose a test statistic that carries out a multi-level thresholding on maximum likelihood estimators (MLEs) of the signals, based on a new Cram\'{e}r type moderate deviation result for multi-dimensional MLEs. Based on the multi-level thresholding test, a multiple testing procedure is proposed for signal identification. Numerical simulations and a case study on maize RNA-seq data are conducted to demonstrate the effectiveness of the proposed approaches on signal detection and identification.