Examples of mikera.matrixx.decompose.IQRResult

mikera.matrixx.decompose.IQRResult
QR decompositions decompose a rectangular matrix 'A' such that 'A=QR'. Where A ∈ ℜ ^{n × m} , n ≥ m, Q ∈ ℜ ^{n × n} is an orthogonal matrix, and R ∈ ℜ ^{n × m} is an upper triangular matrix. Some implementations of QR decomposition require that A has full rank.

Some features of QR decompositions:
- Can decompose rectangular matrices.
- Numerically stable solutions to least-squares problem, but not as stable as SVD
Orthogonal matrices have the following properties:
- QQ^T=I
- Q^T=Q^-1
@author Peter Abeles

  }
  
  @Test
  public void testIdentity() {
    AMatrix a = IdentityMatrix.create(4);
    IQRResult result = QR.decompose(a);
    validateQR(a,result);
  }

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  }
  
  @Test
  public void testBig() {
    AMatrix a = Matrix.createRandom(30, 30);
    IQRResult result = QR.decompose(a);
    validateQR(a, result);
  }

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  }
  
  @Test
  public void testTall() {
    AMatrix a = Matrix.createRandom(5, 3);
    IQRResult result = QR.decompose(a);
    validateQR(a, result);
  }

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  }
  
  @Test
  public void testWide() {
    AMatrix a = Matrix.createRandom(3, 5);
    IQRResult result = QR.decompose(a);
    validateQR(a, result);
  }

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