成人VR视频

Title:

Detection of Multiple Influential Observations on Variable Selection for High-dimensional Data: New Perspective with an Application to Neurologic Signature of Physical Pain.

Abstract:

Influential diagnosis is an integral part of data analysis, of which most existing methodological frameworks presume a deterministic submodel and are designed for low-dimensional data (i.e., the number of predictors聽p smaller than the sample size听苍). However, the stochastic selection of a submodel from high-dimensional data where聽p exceeds听苍 has become ubiquitous. Thus, methods for identifying observations that could exert undue influence on the choice of a submodel can play an important role in this setting. To date, discussion of this topic has been limited, falling short in two domains: (1) constrained ability to detect multiple influential points, and (2) applicability only in restrictive settings. In this talk, building on a recently proposed measure, we introduce a generalized version accommodating different model selectors, the asymptotic property of which is subsequently examined for large聽p. The听碍-means clustering is incorporated into our scheme to detect multiple influential points. Simulation is then conducted to assess the performances of various diagnostic approaches. The proposed procedure further demonstrates its value in improving predictive power when analyzing thermal-stimulated pain based on fMRI data. In addition, the latest development revolving around this newly proposed measure is also presented. This work is conducted under the joint supervision of Professors Masoud Asgharian and Martin Lindquist.

Speaker

Dongliang Zhang is a PhD candidate in the Department of Biostatistics at the Bloomberg School of Public Health, Johns Hopkins University, working under the joint supervision of Professors Martin Lindquist and Masoud Asgharian. Prior to his doctoral study, he obtained his bachelor鈥檚 and master鈥檚 degrees respectively in Honors Probability and Statistics, and Mathematics and Statistics, at the Department of Mathematics and Statistics, 成人VR视频. His research interest revolves around large聽p听蝉尘补濒濒听n problems with application to brain imaging data, and he is a fan of Montreal Canadiens.