On the regularity conditions and applications for generalized likelihood ratio method

We compare different sets of regularity conditions required to derive a generalized likelihood ratio method (GLRM) proposed by Peng et al. (2016a), and present additional applications of GLRM. A numerical experiment substantiates that the GLRM can address a broad set of sensitivity estimation problems in a unified framework.