Exceptions to special case of binomial inverse theorem involving $(A-B)^{-1}$?












1












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Under the Woodbury matrix identity page on Wikipedia, there is a special case under the binomial inverse section where $$(A-B)^{-1}=sum_{k=0}^infty (A^{-1}B)^{k}A^{-1}label{a}tag{1}$$



In my case, I was trying to apply it where $A=I$, which I believe simplifies nicely to $$=sum_{k=0}^infty B^klabel{b}tag{2}$$



At first, it seemed to work fine, but when testing it with random data sets, I started get obscenely large numbers in the resulting matrix. A simple case of when it seems to fail consistently is when the values of the square matrix $B$ are in the interval $[1,infty)$. At that point, the simplification seems to lead all elements of the result to infinity as $k$ goes to infinity, which when summed together, is clearly is not the inverse.



I am able to verify this in code (using R) just generating random values for $B$. I can solve for the inverse of $(I-Q)$ using built in functions and confirm the results by multiplying it by $(I-Q)$ to get $I$, but when I try to manually calculate using $ref{b}$ it falls apart.



Are there exceptions or rules somewhere for $ref{a}$ that I'm missing and inadvertently violating?










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  • $begingroup$
    You have a similar problem even with the binomial theorem over real numbers; take $(1 - 2)^{-1},$ for example, and expand it by the binomial formula.
    $endgroup$
    – David K
    Dec 20 '18 at 16:15












  • $begingroup$
    Check out Neumann series.
    $endgroup$
    – A.Γ.
    Dec 20 '18 at 16:19










  • $begingroup$
    The infinite sum $sum_{k=0}^infty C^k$ converges if and only if $|C|<1$, so $|A^{-1}B|<1$ is a necessary condition you need for (1) to hold.
    $endgroup$
    – Mike Earnest
    Dec 20 '18 at 16:24






  • 1




    $begingroup$
    @MikeEarnest Norm bound by one is sufficient, but not necessary for convergence.
    $endgroup$
    – A.Γ.
    Dec 20 '18 at 16:29
















1












$begingroup$


Under the Woodbury matrix identity page on Wikipedia, there is a special case under the binomial inverse section where $$(A-B)^{-1}=sum_{k=0}^infty (A^{-1}B)^{k}A^{-1}label{a}tag{1}$$



In my case, I was trying to apply it where $A=I$, which I believe simplifies nicely to $$=sum_{k=0}^infty B^klabel{b}tag{2}$$



At first, it seemed to work fine, but when testing it with random data sets, I started get obscenely large numbers in the resulting matrix. A simple case of when it seems to fail consistently is when the values of the square matrix $B$ are in the interval $[1,infty)$. At that point, the simplification seems to lead all elements of the result to infinity as $k$ goes to infinity, which when summed together, is clearly is not the inverse.



I am able to verify this in code (using R) just generating random values for $B$. I can solve for the inverse of $(I-Q)$ using built in functions and confirm the results by multiplying it by $(I-Q)$ to get $I$, but when I try to manually calculate using $ref{b}$ it falls apart.



Are there exceptions or rules somewhere for $ref{a}$ that I'm missing and inadvertently violating?










share|cite|improve this question









$endgroup$












  • $begingroup$
    You have a similar problem even with the binomial theorem over real numbers; take $(1 - 2)^{-1},$ for example, and expand it by the binomial formula.
    $endgroup$
    – David K
    Dec 20 '18 at 16:15












  • $begingroup$
    Check out Neumann series.
    $endgroup$
    – A.Γ.
    Dec 20 '18 at 16:19










  • $begingroup$
    The infinite sum $sum_{k=0}^infty C^k$ converges if and only if $|C|<1$, so $|A^{-1}B|<1$ is a necessary condition you need for (1) to hold.
    $endgroup$
    – Mike Earnest
    Dec 20 '18 at 16:24






  • 1




    $begingroup$
    @MikeEarnest Norm bound by one is sufficient, but not necessary for convergence.
    $endgroup$
    – A.Γ.
    Dec 20 '18 at 16:29














1












1








1





$begingroup$


Under the Woodbury matrix identity page on Wikipedia, there is a special case under the binomial inverse section where $$(A-B)^{-1}=sum_{k=0}^infty (A^{-1}B)^{k}A^{-1}label{a}tag{1}$$



In my case, I was trying to apply it where $A=I$, which I believe simplifies nicely to $$=sum_{k=0}^infty B^klabel{b}tag{2}$$



At first, it seemed to work fine, but when testing it with random data sets, I started get obscenely large numbers in the resulting matrix. A simple case of when it seems to fail consistently is when the values of the square matrix $B$ are in the interval $[1,infty)$. At that point, the simplification seems to lead all elements of the result to infinity as $k$ goes to infinity, which when summed together, is clearly is not the inverse.



I am able to verify this in code (using R) just generating random values for $B$. I can solve for the inverse of $(I-Q)$ using built in functions and confirm the results by multiplying it by $(I-Q)$ to get $I$, but when I try to manually calculate using $ref{b}$ it falls apart.



Are there exceptions or rules somewhere for $ref{a}$ that I'm missing and inadvertently violating?










share|cite|improve this question









$endgroup$




Under the Woodbury matrix identity page on Wikipedia, there is a special case under the binomial inverse section where $$(A-B)^{-1}=sum_{k=0}^infty (A^{-1}B)^{k}A^{-1}label{a}tag{1}$$



In my case, I was trying to apply it where $A=I$, which I believe simplifies nicely to $$=sum_{k=0}^infty B^klabel{b}tag{2}$$



At first, it seemed to work fine, but when testing it with random data sets, I started get obscenely large numbers in the resulting matrix. A simple case of when it seems to fail consistently is when the values of the square matrix $B$ are in the interval $[1,infty)$. At that point, the simplification seems to lead all elements of the result to infinity as $k$ goes to infinity, which when summed together, is clearly is not the inverse.



I am able to verify this in code (using R) just generating random values for $B$. I can solve for the inverse of $(I-Q)$ using built in functions and confirm the results by multiplying it by $(I-Q)$ to get $I$, but when I try to manually calculate using $ref{b}$ it falls apart.



Are there exceptions or rules somewhere for $ref{a}$ that I'm missing and inadvertently violating?







linear-algebra matrices






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asked Dec 20 '18 at 16:09









anjamaanjama

233




233












  • $begingroup$
    You have a similar problem even with the binomial theorem over real numbers; take $(1 - 2)^{-1},$ for example, and expand it by the binomial formula.
    $endgroup$
    – David K
    Dec 20 '18 at 16:15












  • $begingroup$
    Check out Neumann series.
    $endgroup$
    – A.Γ.
    Dec 20 '18 at 16:19










  • $begingroup$
    The infinite sum $sum_{k=0}^infty C^k$ converges if and only if $|C|<1$, so $|A^{-1}B|<1$ is a necessary condition you need for (1) to hold.
    $endgroup$
    – Mike Earnest
    Dec 20 '18 at 16:24






  • 1




    $begingroup$
    @MikeEarnest Norm bound by one is sufficient, but not necessary for convergence.
    $endgroup$
    – A.Γ.
    Dec 20 '18 at 16:29


















  • $begingroup$
    You have a similar problem even with the binomial theorem over real numbers; take $(1 - 2)^{-1},$ for example, and expand it by the binomial formula.
    $endgroup$
    – David K
    Dec 20 '18 at 16:15












  • $begingroup$
    Check out Neumann series.
    $endgroup$
    – A.Γ.
    Dec 20 '18 at 16:19










  • $begingroup$
    The infinite sum $sum_{k=0}^infty C^k$ converges if and only if $|C|<1$, so $|A^{-1}B|<1$ is a necessary condition you need for (1) to hold.
    $endgroup$
    – Mike Earnest
    Dec 20 '18 at 16:24






  • 1




    $begingroup$
    @MikeEarnest Norm bound by one is sufficient, but not necessary for convergence.
    $endgroup$
    – A.Γ.
    Dec 20 '18 at 16:29
















$begingroup$
You have a similar problem even with the binomial theorem over real numbers; take $(1 - 2)^{-1},$ for example, and expand it by the binomial formula.
$endgroup$
– David K
Dec 20 '18 at 16:15






$begingroup$
You have a similar problem even with the binomial theorem over real numbers; take $(1 - 2)^{-1},$ for example, and expand it by the binomial formula.
$endgroup$
– David K
Dec 20 '18 at 16:15














$begingroup$
Check out Neumann series.
$endgroup$
– A.Γ.
Dec 20 '18 at 16:19




$begingroup$
Check out Neumann series.
$endgroup$
– A.Γ.
Dec 20 '18 at 16:19












$begingroup$
The infinite sum $sum_{k=0}^infty C^k$ converges if and only if $|C|<1$, so $|A^{-1}B|<1$ is a necessary condition you need for (1) to hold.
$endgroup$
– Mike Earnest
Dec 20 '18 at 16:24




$begingroup$
The infinite sum $sum_{k=0}^infty C^k$ converges if and only if $|C|<1$, so $|A^{-1}B|<1$ is a necessary condition you need for (1) to hold.
$endgroup$
– Mike Earnest
Dec 20 '18 at 16:24




1




1




$begingroup$
@MikeEarnest Norm bound by one is sufficient, but not necessary for convergence.
$endgroup$
– A.Γ.
Dec 20 '18 at 16:29




$begingroup$
@MikeEarnest Norm bound by one is sufficient, but not necessary for convergence.
$endgroup$
– A.Γ.
Dec 20 '18 at 16:29










1 Answer
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$begingroup$

We will indeed have $(I - B)^{-1} = sum_{k=0}^infty B^k$ whenever the sum on the right converges. This sum will converge if and only if the eigenvalues of $B$ all have magnitude strictly less than $1$.



The equation on wikipedia should have a blurb to the effect of "whenever the sum on the right converges".





A $1 times 1$ example that illustrates what's going on: note that
$$
frac 1{1-x} = 1 + x cdot frac{1}{1 - x}
$$

this equation has a "recursive structure", so we could also write
$$
frac 1{1-x} = 1 + x cdot left[1 + x cdot frac{1}{1 - x}right]\
= 1 + x + x^2 cdot frac 1{1-x}
$$

so that in general, we have
$$
frac 1{1 - x} = 1 + x + x^2 + x^3 + cdots + x^n cdot frac 1{1-x}
$$

Now, whenever the expression on the right approaches a limit, we could also write
$$
frac 1{1 - x} = 1 + x + x^2 + x^3 + cdots = sum_{k=0}^infty x^k
$$

this manipulation only makes sense rigorously (i.e. says something accurate in terms of the usual notion of a limit) when $|x| < 1$.






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    1 Answer
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    $begingroup$

    We will indeed have $(I - B)^{-1} = sum_{k=0}^infty B^k$ whenever the sum on the right converges. This sum will converge if and only if the eigenvalues of $B$ all have magnitude strictly less than $1$.



    The equation on wikipedia should have a blurb to the effect of "whenever the sum on the right converges".





    A $1 times 1$ example that illustrates what's going on: note that
    $$
    frac 1{1-x} = 1 + x cdot frac{1}{1 - x}
    $$

    this equation has a "recursive structure", so we could also write
    $$
    frac 1{1-x} = 1 + x cdot left[1 + x cdot frac{1}{1 - x}right]\
    = 1 + x + x^2 cdot frac 1{1-x}
    $$

    so that in general, we have
    $$
    frac 1{1 - x} = 1 + x + x^2 + x^3 + cdots + x^n cdot frac 1{1-x}
    $$

    Now, whenever the expression on the right approaches a limit, we could also write
    $$
    frac 1{1 - x} = 1 + x + x^2 + x^3 + cdots = sum_{k=0}^infty x^k
    $$

    this manipulation only makes sense rigorously (i.e. says something accurate in terms of the usual notion of a limit) when $|x| < 1$.






    share|cite|improve this answer









    $endgroup$


















      3












      $begingroup$

      We will indeed have $(I - B)^{-1} = sum_{k=0}^infty B^k$ whenever the sum on the right converges. This sum will converge if and only if the eigenvalues of $B$ all have magnitude strictly less than $1$.



      The equation on wikipedia should have a blurb to the effect of "whenever the sum on the right converges".





      A $1 times 1$ example that illustrates what's going on: note that
      $$
      frac 1{1-x} = 1 + x cdot frac{1}{1 - x}
      $$

      this equation has a "recursive structure", so we could also write
      $$
      frac 1{1-x} = 1 + x cdot left[1 + x cdot frac{1}{1 - x}right]\
      = 1 + x + x^2 cdot frac 1{1-x}
      $$

      so that in general, we have
      $$
      frac 1{1 - x} = 1 + x + x^2 + x^3 + cdots + x^n cdot frac 1{1-x}
      $$

      Now, whenever the expression on the right approaches a limit, we could also write
      $$
      frac 1{1 - x} = 1 + x + x^2 + x^3 + cdots = sum_{k=0}^infty x^k
      $$

      this manipulation only makes sense rigorously (i.e. says something accurate in terms of the usual notion of a limit) when $|x| < 1$.






      share|cite|improve this answer









      $endgroup$
















        3












        3








        3





        $begingroup$

        We will indeed have $(I - B)^{-1} = sum_{k=0}^infty B^k$ whenever the sum on the right converges. This sum will converge if and only if the eigenvalues of $B$ all have magnitude strictly less than $1$.



        The equation on wikipedia should have a blurb to the effect of "whenever the sum on the right converges".





        A $1 times 1$ example that illustrates what's going on: note that
        $$
        frac 1{1-x} = 1 + x cdot frac{1}{1 - x}
        $$

        this equation has a "recursive structure", so we could also write
        $$
        frac 1{1-x} = 1 + x cdot left[1 + x cdot frac{1}{1 - x}right]\
        = 1 + x + x^2 cdot frac 1{1-x}
        $$

        so that in general, we have
        $$
        frac 1{1 - x} = 1 + x + x^2 + x^3 + cdots + x^n cdot frac 1{1-x}
        $$

        Now, whenever the expression on the right approaches a limit, we could also write
        $$
        frac 1{1 - x} = 1 + x + x^2 + x^3 + cdots = sum_{k=0}^infty x^k
        $$

        this manipulation only makes sense rigorously (i.e. says something accurate in terms of the usual notion of a limit) when $|x| < 1$.






        share|cite|improve this answer









        $endgroup$



        We will indeed have $(I - B)^{-1} = sum_{k=0}^infty B^k$ whenever the sum on the right converges. This sum will converge if and only if the eigenvalues of $B$ all have magnitude strictly less than $1$.



        The equation on wikipedia should have a blurb to the effect of "whenever the sum on the right converges".





        A $1 times 1$ example that illustrates what's going on: note that
        $$
        frac 1{1-x} = 1 + x cdot frac{1}{1 - x}
        $$

        this equation has a "recursive structure", so we could also write
        $$
        frac 1{1-x} = 1 + x cdot left[1 + x cdot frac{1}{1 - x}right]\
        = 1 + x + x^2 cdot frac 1{1-x}
        $$

        so that in general, we have
        $$
        frac 1{1 - x} = 1 + x + x^2 + x^3 + cdots + x^n cdot frac 1{1-x}
        $$

        Now, whenever the expression on the right approaches a limit, we could also write
        $$
        frac 1{1 - x} = 1 + x + x^2 + x^3 + cdots = sum_{k=0}^infty x^k
        $$

        this manipulation only makes sense rigorously (i.e. says something accurate in terms of the usual notion of a limit) when $|x| < 1$.







        share|cite|improve this answer












        share|cite|improve this answer



        share|cite|improve this answer










        answered Dec 20 '18 at 16:31









        OmnomnomnomOmnomnomnom

        128k791185




        128k791185






























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