Zobrazeno 1 - 10
of 165
pro vyhledávání: '"Rosen, Ori"'
With rapid development of techniques to measure brain activity and structure, statistical methods for analyzing modern brain-imaging play an important role in the advancement of science. Imaging data that measure brain function are usually multivaria
Externí odkaz:
http://arxiv.org/abs/2301.01373
Autor:
Bedoui, Adel, Rosen, Ori
In this paper, we propose a nonparametric Bayesian approach for Lindsey and penalized Gaussian mixtures methods. We compare these methods with the Dirichlet process mixture model. Our approach is a Bayesian nonparametric method not based solely on a
Externí odkaz:
http://arxiv.org/abs/2011.13800
Autor:
Chin, Vincent, Samia, Noelle I., Marchant, Roman, Rosen, Ori, Ioannidis, John P. A., Tanner, Martin A., Cripps, Sally
Forecasting models have been influential in shaping decision-making in the COVID-19 pandemic. However, there is concern that their predictions may have been misleading. Here, we dissect the predictions made by four models for the daily COVID-19 death
Externí odkaz:
http://arxiv.org/abs/2006.15997
This paper provides a formal evaluation of the predictive performance of a model (and its various updates) developed by the Institute for Health Metrics and Evaluation (IHME) for predicting daily deaths attributed to COVID19 for each state in the Uni
Externí odkaz:
http://arxiv.org/abs/2004.04734
This article introduces a nonparametric approach to spectral analysis of a high-dimensional multivariate nonstationary time series. The procedure is based on a novel frequency-domain factor model that provides a flexible yet parsimonious representati
Externí odkaz:
http://arxiv.org/abs/1910.12126
We present a method for the joint analysis of a panel of possibly nonstationary time series. The approach is Bayesian and uses a covariate-dependent infinite mixture model to incorporate multiple time series, with mixture components parameterized by
Externí odkaz:
http://arxiv.org/abs/1908.06622
Naveau et al. (2016) have recently developed a class of methods, based on extreme-value theory (EVT), for capturing low, moderate, and heavy rainfall simultaneously, without the need to choose a threshold typical to EVT methods. We analyse the perfor
Externí odkaz:
http://arxiv.org/abs/1804.08807
This article considers the problem of analyzing associations between power spectra of multiple time series and cross-sectional outcomes when data are observed from multiple subjects. The motivating application comes from sleep medicine, where researc
Externí odkaz:
http://arxiv.org/abs/1502.03153
Publikováno v:
Biostatistics; Jul2024, Vol. 25 Issue 3, p666-680, 15p
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