下平英寿氏 (京都大学・理研AIP)/Hidetoshi SHIMODAIRA (Kyoto Uviv.・RIKEN AIP)
Title:Selective inference for the problem of regions via multiscale bootstrap resampling with applications to hierarchical clustering and lasso
Abstract:Selective inference procedures are considered for computing approximately unbiased p-values for arbitrary shaped hypotheses which are selected after looking at the data. Our idea is to estimate the geometric quantities, namely,
signed distance andmean curvature, by the multiscale bootstrap in which we change the sample size of bootstrap replicates.
Our method is second-order accurate in the large sample theory of smooth boundary surfaces of the hypothesis regions, and it is also justified for regions with nonsmooth surfaces such as cones.
This is joint work with Yoshikazu Terada (Osaka University / RIKEN AIP).