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  21.                                     API Documentation <b class="caret"></b></a><ul class="dropdown-menu">
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  22. <li><a>Packages</a></li>
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  23. <li><a href="packages/Default.html"><i class="icon-folder-open"></i> Default</a></li>
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  24. <li><a href="packages/JAMA.html"><i class="icon-folder-open"></i> JAMA</a></li>
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  25. <li><a href="packages/JAMA%0D%0ACholesky%20decomposition%20class%0D%0AFor%20a%20symmetric,%20positive%20definite%20matrix%20A,%20the%20Cholesky%20decomposition%0D%0Ais%20an%20lower%20triangular%20matrix%20L%20so%20that%20A%20=%20L*L'.html"><i class="icon-folder-open"></i> JAMA

    26. 

  26. Cholesky decomposition class

    27. 

  27. For a symmetric, positive definite matrix A, the Cholesky decomposition

    28. 

  28. is an lower triangular matrix L so that A = L*L'</a></li>
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  29. <li><a href="packages/JAMA%0D%0AClass%20to%20obtain%20eigenvalues%20and%20eigenvectors%20of%20a%20real%20matrix.html"><i class="icon-folder-open"></i> JAMA

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  30. Class to obtain eigenvalues and eigenvectors of a real matrix</a></li>
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  31. <li><a href="packages/JAMA%0D%0AError%20handling.html"><i class="icon-folder-open"></i> JAMA

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  32. Error handling</a></li>
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  33. <li><a href="packages/JAMA%0D%0AFor%20an%20m-by-n%20matrix%20A%20with%20m%20&gt;=%20n,%20the%20LU%20decomposition%20is%20an%20m-by-n%0D%0Aunit%20lower%20triangular%20matrix%20L,%20an%20n-by-n%20upper%20triangular%20matrix%20U,%0D%0Aand%20a%20permutation%20vector%20piv%20of%20length%20m%20so%20that%20A(piv,:)%20=%20L*U.html"><i class="icon-folder-open"></i> JAMA

    34. 

  34. For an m-by-n matrix A with m &gt;= n, the LU decomposition is an m-by-n

    35. 

  35. unit lower triangular matrix L, an n-by-n upper triangular matrix U,

    36. 

  36. and a permutation vector piv of length m so that A(piv,:) = L*U</a></li>
    37. 

  37. <li><a href="packages/JAMA%0D%0AFor%20an%20m-by-n%20matrix%20A%20with%20m%20&gt;=%20n,%20the%20QR%20decomposition%20is%20an%20m-by-n%0D%0Aorthogonal%20matrix%20Q%20and%20an%20n-by-n%20upper%20triangular%20matrix%20R%20so%20that%0D%0AA%20=%20Q*R.html"><i class="icon-folder-open"></i> JAMA

    38. 

  38. For an m-by-n matrix A with m &gt;= n, the QR decomposition is an m-by-n

    39. 

  39. orthogonal matrix Q and an n-by-n upper triangular matrix R so that

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  40. A = Q*R</a></li>
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  41. <li><a href="packages/JAMA%0D%0AFor%20an%20m-by-n%20matrix%20A%20with%20m%20&gt;=%20n,%20the%20singular%20value%20decomposition%20is%0D%0Aan%20m-by-n%20orthogonal%20matrix%20U,%20an%20n-by-n%20diagonal%20matrix%20S,%20and%0D%0Aan%20n-by-n%20orthogonal%20matrix%20V%20so%20that%20A%20=%20U*S*V'.html"><i class="icon-folder-open"></i> JAMA

    42. 

  42. For an m-by-n matrix A with m &gt;= n, the singular value decomposition is

    43. 

  43. an m-by-n orthogonal matrix U, an n-by-n diagonal matrix S, and

    44. 

  44. an n-by-n orthogonal matrix V so that A = U*S*V'</a></li>
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  45. <li><a href="packages/JAMA%0D%0APythagorean%20Theorem:%0D%0Aa%20=%203%0D%0Ab%20=%204%0D%0Ar%20=%20sqrt(square(a)%20+%20square(b))%0D%0Ar%20=%205%0D%0Ar%20=%20sqrt(a%5E2%20+%20b%5E2)%20without%20under.overflow.html"><i class="icon-folder-open"></i> JAMA

    46. 

  46. Pythagorean Theorem:

    47. 

  47. a = 3

    48. 

  48. b = 4

    49. 

  49. r = sqrt(square(a) + square(b))

    50. 

  50. r = 5

    51. 

  51. r = sqrt(a^2 + b^2) without under/overflow</a></li>
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  52. <li><a href="packages/PHPExcel.html"><i class="icon-folder-open"></i> PHPExcel</a></li>
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  57.                                     Charts <b class="caret"></b></a><ul class="dropdown-menu"><li><a href="graph_class.html"><i class="icon-list-alt"></i> Class hierarchy diagram</a></li></ul>
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