Difference between revisions of "Manuals/calci/CHOLESKY"

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:<h2>Algorithm</h2>
 
:<h2>Algorithm</h2>
##Determine <math>l_{11}</math> and <math>L_{21}</math>
+
<ol>
 +
<li>Determine <math>l_{11}</math> and <math>L_{21}</math></li>
 
<math>l_{11}</math> = <math>\sqrt{a_{11}}</math>
 
<math>l_{11}</math> = <math>\sqrt{a_{11}}</math>
 
<math>L_{21}</math> = <math>\frac{1}{l_{11}}A_{21}</math>
 
<math>L_{21}</math> = <math>\frac{1}{l_{11}}A_{21}</math>
##Compute <math>L_{22}</math> from  
+
<li>Compute <math>L_{22}</math> from </li>
 
<math>A_{22}-L_{21}L_{21}^{T}</math> = <math>L_{22}L_{22}^{T}</math>
 
<math>A_{22}-L_{21}L_{21}^{T}</math> = <math>L_{22}L_{22}^{T}</math>
 
*this is a Cholesky Factorization of order <math>n-1</math>
 
*this is a Cholesky Factorization of order <math>n-1</math>
 +
<ol>
  
 
==ZOS Section==
 
==ZOS Section==

Revision as of 06:40, 10 April 2015

CHOLESKY(arr)


  • is the array of numeric elements

Description

  • This function gives the value of Cholesky factorization.
  • It is called Cholesky Decomposition or Cholesky Factorization.
  • The Cholesky Factorization is only defined for symmetric or Hermitian positive definite matrices.
  • Every positive definite matrix A can be factored as =
 is lower triangular with positive diagonal elements
 is is the conjugate transpose value of 
  • Every Hermitian positive-definite matrix has a unique Cholesky decomposition.
  • Here , is set of values to find the factorization value.
  • Partition matrices in = is

Algorithm

  1. Determine and
  2. = =
  3. Compute from
  4. =
    • this is a Cholesky Factorization of order

      ZOS Section

      Examples

      1. =CHOLESKY([[16,32,12],[12, 18, 0],[ -5, 0, 11]])

      Result
      4 0 0
      3 3 0
      -1.25 1.25 2.80624

      2. =CHOLESKY([[25, 15, -5],[15, 18, 0],[ -5, 0, 11]])

      Result
      5 0 0
      3 3 0
      -1 1 3

      See Also