Browsing Master's Degree in Data Science by Title

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  • Höllwirth, Hans-Peter (2017)
    This paper studies a novel particle filter method proposed by Brownlees and Kristensen (2017) for parameter estimation of nonlinear state space models. The particle filter, named Importance Sampling Particle Filter, is tested ...
  • Lange, Robert Tjarko (2017)
    Data scientific questions face the fundamental trade-off between complexity, generalizability and computational feasibility. The need for quick estimation and evaluation of a vast amount of statistical models has given ...
  • Hao, Kwa Jie (2018)
    Hierarchical modeling is a practical approach with proven results in modeling real world data. This paper studies Gaussian hierarchical models and methods which exploit the sparse conditional independence structure of such ...

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