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Comparative study of clustering techniques for real‐time dynamic model reduction Early View

  • Journal: Statistical Analysis and Data Mining: The ASA Data Science Journal
  • Authors: Emilie Purvine, Eduardo Cotilla‐Sanchez, Mahantesh Halappanavar, Zhenyu Huang, Guang Lin, Shuai Lu, Shaobu Wang
  • Published Date: Aug 24, 2017

Dynamic model reduction in power systems is necessary for improving computational efficiency. Traditional model reduction using linearized models or offline analysis is not adequate to...

Joining statistics and geophysics for assessment and uncertainty quantification of three‐dimensional seismic Earth models Early View

  • Journal: Statistical Analysis and Data Mining: The ASA Data Science Journal
  • Authors: Carène Larmat, Monica Maceira, David M. Higdon, Dale N. Anderson
  • Published Date: Aug 29, 2017

Seismic inversions produce seismic models, which are 3‐dimensional (3D) images of wave velocity of the entire planet retrieved by fitting seismic measurements made on records of past...

Clustering over‐dispersed data with mixed feature types Early View

  • Journal: Statistical Analysis and Data Mining: The ASA Data Science Journal
  • Authors: Lu Wang, Dongxiao Zhu, Ming Dong
  • Published Date: Jan 10, 2018

Despite many data clustering methods are available, most of them uncover compactness or connectivity as the intrinsic structure of unlabeled data. Very few approaches explicitly consider...

Sparse estimation of multivariate Poisson log‐normal models from count data Early View

  • Journal: Statistical Analysis and Data Mining: The ASA Data Science Journal
  • Authors: Hao Wu, Xinwei Deng, Naren Ramakrishnan
  • Published Date: Jan 10, 2018

Modeling data with multivariate count responses is a challenging problem because of the discrete nature of the responses. Existing methods for univariate count response cannot be easily...

Informative priors in Bayesian inference and computation Early View

  • Journal: Statistical Analysis and Data Mining: The ASA Data Science Journal
  • Authors: Shirin Golchi
  • Published Date: Jan 19, 2018

The use of prior distributions is often a controversial topic in Bayesian inference. Informative priors are often avoided at all costs. However, when prior information is available,...

Sequential optimal positioning of mobile sensors using mutual information Early View

  • Journal: Statistical Analysis and Data Mining: The ASA Data Science Journal
  • Authors: Kathleen Schmidt, Ralph C. Smith, Jason Hite, John Mattingly, Yousry Azmy, Deepak Rajan, Ryan Goldhahn
  • Published Date: Jul 19, 2019

Abstract Source localization, such as detecting a nuclear source in an urban area or ascertaining the origin of a chemical plume, is generally regarded as a well‐documented inverse problem; however,...

Making social networks more human: A topological approach Early View

  • Journal: Statistical Analysis and Data Mining: The ASA Data Science Journal
  • Authors: Jonathan W. Berry, Cynthia A. Phillips, Jared Saia
  • Published Date: Jul 24, 2019

Abstract A key problem in social network analysis is to identify nonhuman interactions. State‐of‐the‐art bot‐detection systems like Botometer train machine‐learning models on user‐specific data....

Gaussian mixture models as automated particle classifiers for fast neutron detectors Early View

  • Journal: Statistical Analysis and Data Mining: The ASA Data Science Journal
  • Authors: Brenton Blair, Cliff Chen, Andrew Glenn, Alan Kaplan, Jaime Ruz, Lance Simms, Ron Wurtz
  • Published Date: Jul 25, 2019

Abstract Pulse shape discrimination (PSD) is the task of classifying electronic pulse shapes for different particle types such as gamma rays and fast neutrons interacting in scintillators and read out...

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