Compressed principal component analysis of non-gaussian vectors

Mathematics

• Principal Component Analysis 77%
• Random Vector 72%
• Eigenvector 40%
• Random Coefficients 34%
• Polynomial 30%
• Covariance matrix 26%
• Linear Combination 25%
• Target 25%
• Discrete random variable 18%
• Independent Random Variables 15%
• Symmetric Functions 15%
• Approximation 14%
• Coefficient 14%
• Directly proportional 12%
• Express 12%
• Random variable 10%
• Unit 10%
• Eigenvalue 9%
• Demonstrate 8%
• Framework 8%
• Zero 7%
• Model 4%

Business & Economics

• Principal Component Analysis 100%
• Polynomials 35%
• Random Coefficients 23%
• Covariance Matrix 20%
• Random Variables 18%
• Approximation 15%
• Coefficients 13%
• Eigenvalues 11%

Engineering & Materials Science

• Principal component analysis 69%
• Eigenvalues and eigenfunctions 28%
• Polynomials 28%
• Random variables 18%
• Covariance matrix 18%
• Set theory 5%