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作者：Richardson, Thomas S.; Robins, James M.; Wang, Linbo
作者单位：University of Washington; University of Washington Seattle; Harvard University; Harvard T.H. Chan School of Public Health; Harvard University; Harvard T.H. Chan School of Public Health; University of Washington; University of Washington Seattle
摘要：A common problem in formulating models for the relative risk and risk difference is the variation dependence between these parameters and the baseline risk, which is a nuisance model. We address this problem by proposing the conditional log odds-product as a preferred nuisance model. This novel nuisance model facilitates maximum-likelihood estimation, but also permits doubly-robust estimation for the parameters of interest. Our approach is illustrated via simulations and a data analysis. An R ...
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作者：Shephard, Neil; Yang, Justin J.
作者单位：Harvard University; Harvard University
摘要：This article proposes a novel model of financial prices where (i) prices are discrete; (ii) prices change in continuous time; (iii) a high proportion of price changes are reversed in a fraction of a second. Our model is analytically tractable and directly formulated in terms of the calendar time and price impact curve. The resulting cadlag price process is a piecewise constant semimartingale with finite activity, finite variation, and no Brownian motion component. We use moment-based estimatio...
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作者：Wang, Xiao; Zhu, Hongtu
作者单位：Purdue University System; Purdue University; University of North Carolina; University of North Carolina Chapel Hill
摘要：The use of imaging markers to predict clinical outcomes can have a great impact in public health. The aim of this article is to develop a class of generalized scalar-on-image regression models via total variation (GSIRM-TV), in the sense of generalized linear models, for scalar response and imaging predictor with the presence of scalar covariates. A key novelty of GSIRM-TV is that it is assumed that the slope function (or image) of GSIRM-TV belongs to the space of bounded total variation to ex...
