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Using R: Gram-Schmidt Orthonormalization Process
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Classroom Contents
Matrices
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- 1 The Kronecker Product
- 2 The Vec Operator
- 3 The Spectral Decomposition (Eigendecomposition)
- 4 Positive Eigenvalues of X'X and XX' are equal
- 5 The Singular Value Decomposition
- 6 Generalized Inverse Matrix
- 7 Generalized Inverse for a Symmetric Matrix
- 8 The Singular Value Decomposition (part 2)
- 9 Least Squares Inverse Matrix
- 10 The Moore Penrose Pseudoinverse
- 11 Idempotent Matrices
- 12 A Square-Root Matrix
- 13 Extended Cauchy-Schwarz Inequality
- 14 Projection Matrices: Introduction
- 15 Perpendicular Projection Matrix
- 16 Gram-Schmidt Orthonormalization Process: Perpendicular Projection Matrix
- 17 Using R: Gram-Schmidt Orthonormalization Process
- 18 Inverse of a Partitioned Matrix
- 19 Random Vectors and Random Matrices
- 20 2 formulas between the determinant, trace and eigen values of a matrix
- 21 Woodbury Matrix Identity & Sherman-Morrison Formula
- 22 Sum of Perpendicular Projection Matrices
