Derivative of matrix inverse w.r.t. vector












1












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I need to differentiate the inverse of the $Ktimes K$ symmetric matrix $A$ w.r.t some vector (that $A$ depends on). Is there a rule for this? In case I do the derivative w.r.t. to some scalar there's this rule that
$DA^{-1}= -A^{-1}*DA*A^{-1}$.



Is this also valid in case of derivative w.r.t. vector or if not is there something equivalent?



Thanks!










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  • $begingroup$
    You can not derive a matrix with respect to a vector
    $endgroup$
    – Ahmad Bazzi
    Sep 2 '16 at 11:37










  • $begingroup$
    @AhmadBazzi The verb form of derivative is actually differentiate. When one derives something, he extrapolates it only from rudiments and shows it is true.
    $endgroup$
    – Chase Ryan Taylor
    Nov 22 '17 at 6:37
















1












$begingroup$


I need to differentiate the inverse of the $Ktimes K$ symmetric matrix $A$ w.r.t some vector (that $A$ depends on). Is there a rule for this? In case I do the derivative w.r.t. to some scalar there's this rule that
$DA^{-1}= -A^{-1}*DA*A^{-1}$.



Is this also valid in case of derivative w.r.t. vector or if not is there something equivalent?



Thanks!










share|cite|improve this question











$endgroup$












  • $begingroup$
    You can not derive a matrix with respect to a vector
    $endgroup$
    – Ahmad Bazzi
    Sep 2 '16 at 11:37










  • $begingroup$
    @AhmadBazzi The verb form of derivative is actually differentiate. When one derives something, he extrapolates it only from rudiments and shows it is true.
    $endgroup$
    – Chase Ryan Taylor
    Nov 22 '17 at 6:37














1












1








1


1



$begingroup$


I need to differentiate the inverse of the $Ktimes K$ symmetric matrix $A$ w.r.t some vector (that $A$ depends on). Is there a rule for this? In case I do the derivative w.r.t. to some scalar there's this rule that
$DA^{-1}= -A^{-1}*DA*A^{-1}$.



Is this also valid in case of derivative w.r.t. vector or if not is there something equivalent?



Thanks!










share|cite|improve this question











$endgroup$




I need to differentiate the inverse of the $Ktimes K$ symmetric matrix $A$ w.r.t some vector (that $A$ depends on). Is there a rule for this? In case I do the derivative w.r.t. to some scalar there's this rule that
$DA^{-1}= -A^{-1}*DA*A^{-1}$.



Is this also valid in case of derivative w.r.t. vector or if not is there something equivalent?



Thanks!







linear-algebra matrices derivatives






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edited Feb 19 '14 at 19:29









Davide Giraudo

128k17155268




128k17155268










asked Feb 17 '14 at 20:15









dummydummy

364




364












  • $begingroup$
    You can not derive a matrix with respect to a vector
    $endgroup$
    – Ahmad Bazzi
    Sep 2 '16 at 11:37










  • $begingroup$
    @AhmadBazzi The verb form of derivative is actually differentiate. When one derives something, he extrapolates it only from rudiments and shows it is true.
    $endgroup$
    – Chase Ryan Taylor
    Nov 22 '17 at 6:37


















  • $begingroup$
    You can not derive a matrix with respect to a vector
    $endgroup$
    – Ahmad Bazzi
    Sep 2 '16 at 11:37










  • $begingroup$
    @AhmadBazzi The verb form of derivative is actually differentiate. When one derives something, he extrapolates it only from rudiments and shows it is true.
    $endgroup$
    – Chase Ryan Taylor
    Nov 22 '17 at 6:37
















$begingroup$
You can not derive a matrix with respect to a vector
$endgroup$
– Ahmad Bazzi
Sep 2 '16 at 11:37




$begingroup$
You can not derive a matrix with respect to a vector
$endgroup$
– Ahmad Bazzi
Sep 2 '16 at 11:37












$begingroup$
@AhmadBazzi The verb form of derivative is actually differentiate. When one derives something, he extrapolates it only from rudiments and shows it is true.
$endgroup$
– Chase Ryan Taylor
Nov 22 '17 at 6:37




$begingroup$
@AhmadBazzi The verb form of derivative is actually differentiate. When one derives something, he extrapolates it only from rudiments and shows it is true.
$endgroup$
– Chase Ryan Taylor
Nov 22 '17 at 6:37










2 Answers
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$begingroup$

You can find a list of rules for differentiating matrices by vectors or scalars by looking up "Matrix calculus".



A list of such rules is available on Wikipedia here in the "Identities" section.






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    0












    $begingroup$

    Consider some function $A:u=[u_1,cdots,u_k]^Tin mathbb{R}^krightarrow A(u)=[a_{i,j}(u)]in GL_n(mathbb{R})$ and let
    $$f:urightarrow (A(u))^{-1}.$$



    Then $Df_u:h=[h_1,cdots,h_k]^Tinmathbb{R}^krightarrow -A^{-1}(u)DA_u(h)A^{-1}(u)in M_n(mathbb{R})$, where $DA_u(h)=[b_{i,j}(h)]in M_n(mathbb{R})$ (a linear application in $h$) is defined by



    $b_{i,j}(h)=sum_{pleq k} dfrac{partial a_{i,j}(u)}{partial u_p}h_pinmathbb{R}$.






    share|cite|improve this answer









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      2 Answers
      2






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      2 Answers
      2






      active

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      active

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      0












      $begingroup$

      You can find a list of rules for differentiating matrices by vectors or scalars by looking up "Matrix calculus".



      A list of such rules is available on Wikipedia here in the "Identities" section.






      share|cite|improve this answer









      $endgroup$


















        0












        $begingroup$

        You can find a list of rules for differentiating matrices by vectors or scalars by looking up "Matrix calculus".



        A list of such rules is available on Wikipedia here in the "Identities" section.






        share|cite|improve this answer









        $endgroup$
















          0












          0








          0





          $begingroup$

          You can find a list of rules for differentiating matrices by vectors or scalars by looking up "Matrix calculus".



          A list of such rules is available on Wikipedia here in the "Identities" section.






          share|cite|improve this answer









          $endgroup$



          You can find a list of rules for differentiating matrices by vectors or scalars by looking up "Matrix calculus".



          A list of such rules is available on Wikipedia here in the "Identities" section.







          share|cite|improve this answer












          share|cite|improve this answer



          share|cite|improve this answer










          answered Feb 19 '14 at 19:37









          BatmanBatman

          16.5k11735




          16.5k11735























              0












              $begingroup$

              Consider some function $A:u=[u_1,cdots,u_k]^Tin mathbb{R}^krightarrow A(u)=[a_{i,j}(u)]in GL_n(mathbb{R})$ and let
              $$f:urightarrow (A(u))^{-1}.$$



              Then $Df_u:h=[h_1,cdots,h_k]^Tinmathbb{R}^krightarrow -A^{-1}(u)DA_u(h)A^{-1}(u)in M_n(mathbb{R})$, where $DA_u(h)=[b_{i,j}(h)]in M_n(mathbb{R})$ (a linear application in $h$) is defined by



              $b_{i,j}(h)=sum_{pleq k} dfrac{partial a_{i,j}(u)}{partial u_p}h_pinmathbb{R}$.






              share|cite|improve this answer









              $endgroup$


















                0












                $begingroup$

                Consider some function $A:u=[u_1,cdots,u_k]^Tin mathbb{R}^krightarrow A(u)=[a_{i,j}(u)]in GL_n(mathbb{R})$ and let
                $$f:urightarrow (A(u))^{-1}.$$



                Then $Df_u:h=[h_1,cdots,h_k]^Tinmathbb{R}^krightarrow -A^{-1}(u)DA_u(h)A^{-1}(u)in M_n(mathbb{R})$, where $DA_u(h)=[b_{i,j}(h)]in M_n(mathbb{R})$ (a linear application in $h$) is defined by



                $b_{i,j}(h)=sum_{pleq k} dfrac{partial a_{i,j}(u)}{partial u_p}h_pinmathbb{R}$.






                share|cite|improve this answer









                $endgroup$
















                  0












                  0








                  0





                  $begingroup$

                  Consider some function $A:u=[u_1,cdots,u_k]^Tin mathbb{R}^krightarrow A(u)=[a_{i,j}(u)]in GL_n(mathbb{R})$ and let
                  $$f:urightarrow (A(u))^{-1}.$$



                  Then $Df_u:h=[h_1,cdots,h_k]^Tinmathbb{R}^krightarrow -A^{-1}(u)DA_u(h)A^{-1}(u)in M_n(mathbb{R})$, where $DA_u(h)=[b_{i,j}(h)]in M_n(mathbb{R})$ (a linear application in $h$) is defined by



                  $b_{i,j}(h)=sum_{pleq k} dfrac{partial a_{i,j}(u)}{partial u_p}h_pinmathbb{R}$.






                  share|cite|improve this answer









                  $endgroup$



                  Consider some function $A:u=[u_1,cdots,u_k]^Tin mathbb{R}^krightarrow A(u)=[a_{i,j}(u)]in GL_n(mathbb{R})$ and let
                  $$f:urightarrow (A(u))^{-1}.$$



                  Then $Df_u:h=[h_1,cdots,h_k]^Tinmathbb{R}^krightarrow -A^{-1}(u)DA_u(h)A^{-1}(u)in M_n(mathbb{R})$, where $DA_u(h)=[b_{i,j}(h)]in M_n(mathbb{R})$ (a linear application in $h$) is defined by



                  $b_{i,j}(h)=sum_{pleq k} dfrac{partial a_{i,j}(u)}{partial u_p}h_pinmathbb{R}$.







                  share|cite|improve this answer












                  share|cite|improve this answer



                  share|cite|improve this answer










                  answered May 3 '17 at 12:32









                  loup blancloup blanc

                  24.1k21851




                  24.1k21851






























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