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作者：Bornkamp, Bjoern; Bretz, Frank; Dette, Holger; Pinheiro, Jose
作者单位：Dortmund University of Technology; Ruhr University Bochum; Novartis; Johnson & Johnson; Johnson & Johnson USA
摘要：Dose-finding studies are frequently conducted to evaluate the effect of different doses or concentration levels of a compound on a response of interest. Applications include the investigation of a new medicinal drug, a herbicide or fertilizer, a molecular entity, an environmental toxin, or an industrial chemical. In pharmaceutical drug development, dose-finding studies are of critical importance because of regulatory requirements that marketed doses are safe and provide clinically relevant eff...
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作者：Matteson, David S.; McLean, Mathew W.; Woodard, Dawn B.; Henderson, Shane G.
作者单位：Cornell University
摘要：We introduce a new method for forecasting emergency call arrival rates that combines integer-valued time series models with a dynamic latent factor structure. Covariate information is captured via simple constraints on the factor loadings. We directly model the count-valued arrivals per hour, rather than using an artificial assumption of normality. This is crucial for the emergency medical service context, in which the volume of calls may be very low. Smoothing splines are used in estimating t...
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作者：Tancredi, Andrea; Liseo, Brunero
作者单位：Sapienza University Rome
摘要：We propose and illustrate a hierarchical Bayesian approach for matching statistical records observed on different occasions. We show how this model can be profitably adopted both in record linkage problems and in capture-recapture setups, where the size of a finite population is the real object of interest. There are at least two important differences between the proposed model-based approach and the current practice in record linkage. First, the statistical model is built up on the actually o...
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作者：Brynjarsdottir, Jenny; Berliner, L. Mark
作者单位：University System of Ohio; Ohio State University
摘要：We present a Bayesian hierarchical modeling approach to paleoclimate reconstruction using borehole temperature profiles. The approach relies on modeling heat conduction in solids via the heat equation with step function, surface boundary conditions. Our analysis includes model error and assumes that the boundary conditions are random processes. The formulation also enables separation of measurement error and model error. We apply the analysis to data from nine borehole temperature records from...
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作者：Mishchenko, Yuriy; Vogelstein, Joshua T.; Paninski, Liam
作者单位：Columbia University; Columbia University; Johns Hopkins University
摘要：Deducing the structure of neural circuits is one of the central problems of modern neuroscience. Recently-introduced calcium fluorescent imaging methods permit experimentalists to observe network activity in large populations of neurons, but these techniques provide only indirect observations of neural spike trains, with limited time resolution and signal quality. In this work we present a Bayesian approach for inferring neural circuitry given this type of imaging data. We model the network ac...
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作者：Bovy, Jo; Hogg, David W.; Roweis, Sam T.
作者单位：New York University; New York University
摘要：We generalize the well-known mixtures of Gaussians approach to density estimation and the accompanying Expectation-Maximization technique for finding the maximum likelihood parameters of the mixture to the case where each data point carries an individual d-dimensional uncertainty covariance and has unique missing data properties. This algorithm reconstructs the error-deconvolved or underlying distribution function common to all samples, even when the individual data points are samples from dif...
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作者：Bhattacharya, Sourabh; Maitra, Ranjan
作者单位：Indian Statistical Institute; Indian Statistical Institute Kolkata; Iowa State University
摘要：Effective connectivity analysis provides an understanding of the functional organization of the brain by studying how activated regions influence one other. We propose a nonparametric Bayesian approach to model effective connectivity assuming a dynamic nonstationary neuronal system. Our approach uses the Dirichlet process to specify an appropriate (most plausible according to our prior beliefs) dynamic model as the expectation of a set of plausible models upon which we assign a probability dis...
