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作者：Liu, Suyu; Guo, Beibei; Yuan, Ying
作者单位：University of Texas System; UTMD Anderson Cancer Center; Louisiana State University System; Louisiana State University
摘要：Immunotherapy is an innovative treatment approach that stimulates a patient's immune system to fight cancer. It demonstrates characteristics distinct from conventional chemotherapy and stands to revolutionize cancer treatment. We propose a Bayesian phase I/II dose-finding design that incorporates the unique features of immunotherapy by simultaneously considering three outcomes: immune response, toxicity, and efficacy. The objective is to identify the biologically optimal dose, defined as the d...
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作者：Clairon, Quentin; Brunel, Nicolas J. -B.
作者单位：Newcastle University - UK; Universite Paris Saclay; Centre National de la Recherche Scientifique (CNRS); Ecole Nationale Superieure d'Informatique pour l'Industrie et l'Entreprise (ENSIIE); Centre National de la Recherche Scientifique (CNRS); Universite Paris Saclay
摘要：Ordinary differential equations (ODE) are routinely calibrated on real data for estimating unknown parameters or for reverse-engineering. Nevertheless, standard statistical techniques can give disappointing results because of the complex relationship between parameters and states, which makes the corresponding estimation problem ill-posed. Moreover, ODE are mechanistic models that are prone to modeling errors, whose influences on inference are often neglected during statistical analysis. We pr...
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作者：Lee, Sokbae; Liao, Yuan; Seo, Myung Hwan; Shin, Youngki
作者单位：Columbia University; University of London; London School Economics & Political Science; Rutgers University System; Rutgers University New Brunswick; Seoul National University (SNU); University of Technology Sydney; McMaster University
摘要：In this article, we consider a high-dimensional quantile regression model where the sparsity structure may differ between two sub-populations. We develop (1)-penalized estimators of both regression coefficients and the threshold parameter. Our penalized estimators not only select covariates but also discriminate between a model with homogenous sparsity and a model with a change point. As a result, it is not necessary to know or pretest whether the change point is present, or where it occurs. O...
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作者：Park, Jaewoo; Haran, Murali
作者单位：Pennsylvania Commonwealth System of Higher Education (PCSHE); Pennsylvania State University; Pennsylvania State University - University Park
摘要：Models with intractable normalizing functions arise frequently in statistics. Common examples of such models include exponential random graph models for social networks and Markov point processes for ecology and disease modeling. Inference for these models is complicated because the normalizing functions of their probability distributions include the parameters of interest. In Bayesian analysis, they result in so-called doubly intractable posterior distributions which pose significant computat...
