Factor Models and Principal Components

  • Ruppert D
  • Matteson D
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Abstract

High-dimensional data can be challenging to analyze. They are difficult to visualize, need extensive computer resources, and often require special statistical methodology. Fortunately, in many practical applications, high-dimensional data have most of their variation...

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Ruppert, D., & Matteson, D. S. (2015). Factor Models and Principal Components (pp. 517–552). https://doi.org/10.1007/978-1-4939-2614-5_18

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