What lemma for product of derivatives equals the n-derivative?











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Why must one require regularity in order for Fisher information to be $Ebigg( frac{partial^2 l(theta, X)}{partial theta^2} bigg)$?



Rather than



$Ebigg( frac{partial l(theta, X)}{partial theta}frac{partial l(theta, X)}{partial theta}^T bigg)$



Since my notes say that "under sufficient regularity conditions", then:



$I(theta)=Ebigg( frac{partial^2 l(theta, X)}{partial theta^2} bigg)$



However, what's the lemma that says that the product equals 2nd derivative?










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    up vote
    0
    down vote

    favorite












    Why must one require regularity in order for Fisher information to be $Ebigg( frac{partial^2 l(theta, X)}{partial theta^2} bigg)$?



    Rather than



    $Ebigg( frac{partial l(theta, X)}{partial theta}frac{partial l(theta, X)}{partial theta}^T bigg)$



    Since my notes say that "under sufficient regularity conditions", then:



    $I(theta)=Ebigg( frac{partial^2 l(theta, X)}{partial theta^2} bigg)$



    However, what's the lemma that says that the product equals 2nd derivative?










    share|cite|improve this question


























      up vote
      0
      down vote

      favorite









      up vote
      0
      down vote

      favorite











      Why must one require regularity in order for Fisher information to be $Ebigg( frac{partial^2 l(theta, X)}{partial theta^2} bigg)$?



      Rather than



      $Ebigg( frac{partial l(theta, X)}{partial theta}frac{partial l(theta, X)}{partial theta}^T bigg)$



      Since my notes say that "under sufficient regularity conditions", then:



      $I(theta)=Ebigg( frac{partial^2 l(theta, X)}{partial theta^2} bigg)$



      However, what's the lemma that says that the product equals 2nd derivative?










      share|cite|improve this question















      Why must one require regularity in order for Fisher information to be $Ebigg( frac{partial^2 l(theta, X)}{partial theta^2} bigg)$?



      Rather than



      $Ebigg( frac{partial l(theta, X)}{partial theta}frac{partial l(theta, X)}{partial theta}^T bigg)$



      Since my notes say that "under sufficient regularity conditions", then:



      $I(theta)=Ebigg( frac{partial^2 l(theta, X)}{partial theta^2} bigg)$



      However, what's the lemma that says that the product equals 2nd derivative?







      derivatives fisher-information






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      share|cite|improve this question













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      share|cite|improve this question








      edited Nov 21 at 9:47

























      asked Nov 21 at 9:23









      mavavilj

      2,6501932




      2,6501932






















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          My impression is that you got something wrong here. Note that $$frac{partial^2 l(theta, X)}{partial theta^2} $$ is a second derivative, while $$frac{partial l(theta, X)}{partial theta}frac{partial l(theta, X)}{partial theta}^T$$ is a product of two first-order derivatives. As such, they are surely not equal in general: consider for example the function $$l(theta,X) = theta cdot X.$$



          Try reading the wikipedia page on the Fisher information and compare it with your notes.






          share|cite|improve this answer























          • Then what's a lemma that says that they can be equal?
            – mavavilj
            Nov 21 at 9:46










          • @mavavilj I wouldn't look for such a lemma (it would mean that $l$ has to satisfy a certain differential equation for all $X$, which is a very strict limitation), I'd rather try to understand what was meant in your notes. What is the definition of $l$?
            – user159517
            Nov 21 at 9:49










          • The wikipedia says same as my notes: "If log f(x; θ) is twice differentiable with respect to θ, and under certain regularity conditions,[4] then the Fisher information may also be written as". But I want to know what the lemma is that allows for that equality.
            – mavavilj
            Nov 21 at 9:52












          • Cramer-Rao bound? stat.tamu.edu/~suhasini/teaching613/inference.pdf (Theorem 1.1)
            – mavavilj
            Nov 21 at 9:53











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          1 Answer
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          1 Answer
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          active

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          up vote
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          My impression is that you got something wrong here. Note that $$frac{partial^2 l(theta, X)}{partial theta^2} $$ is a second derivative, while $$frac{partial l(theta, X)}{partial theta}frac{partial l(theta, X)}{partial theta}^T$$ is a product of two first-order derivatives. As such, they are surely not equal in general: consider for example the function $$l(theta,X) = theta cdot X.$$



          Try reading the wikipedia page on the Fisher information and compare it with your notes.






          share|cite|improve this answer























          • Then what's a lemma that says that they can be equal?
            – mavavilj
            Nov 21 at 9:46










          • @mavavilj I wouldn't look for such a lemma (it would mean that $l$ has to satisfy a certain differential equation for all $X$, which is a very strict limitation), I'd rather try to understand what was meant in your notes. What is the definition of $l$?
            – user159517
            Nov 21 at 9:49










          • The wikipedia says same as my notes: "If log f(x; θ) is twice differentiable with respect to θ, and under certain regularity conditions,[4] then the Fisher information may also be written as". But I want to know what the lemma is that allows for that equality.
            – mavavilj
            Nov 21 at 9:52












          • Cramer-Rao bound? stat.tamu.edu/~suhasini/teaching613/inference.pdf (Theorem 1.1)
            – mavavilj
            Nov 21 at 9:53















          up vote
          0
          down vote













          My impression is that you got something wrong here. Note that $$frac{partial^2 l(theta, X)}{partial theta^2} $$ is a second derivative, while $$frac{partial l(theta, X)}{partial theta}frac{partial l(theta, X)}{partial theta}^T$$ is a product of two first-order derivatives. As such, they are surely not equal in general: consider for example the function $$l(theta,X) = theta cdot X.$$



          Try reading the wikipedia page on the Fisher information and compare it with your notes.






          share|cite|improve this answer























          • Then what's a lemma that says that they can be equal?
            – mavavilj
            Nov 21 at 9:46










          • @mavavilj I wouldn't look for such a lemma (it would mean that $l$ has to satisfy a certain differential equation for all $X$, which is a very strict limitation), I'd rather try to understand what was meant in your notes. What is the definition of $l$?
            – user159517
            Nov 21 at 9:49










          • The wikipedia says same as my notes: "If log f(x; θ) is twice differentiable with respect to θ, and under certain regularity conditions,[4] then the Fisher information may also be written as". But I want to know what the lemma is that allows for that equality.
            – mavavilj
            Nov 21 at 9:52












          • Cramer-Rao bound? stat.tamu.edu/~suhasini/teaching613/inference.pdf (Theorem 1.1)
            – mavavilj
            Nov 21 at 9:53













          up vote
          0
          down vote










          up vote
          0
          down vote









          My impression is that you got something wrong here. Note that $$frac{partial^2 l(theta, X)}{partial theta^2} $$ is a second derivative, while $$frac{partial l(theta, X)}{partial theta}frac{partial l(theta, X)}{partial theta}^T$$ is a product of two first-order derivatives. As such, they are surely not equal in general: consider for example the function $$l(theta,X) = theta cdot X.$$



          Try reading the wikipedia page on the Fisher information and compare it with your notes.






          share|cite|improve this answer














          My impression is that you got something wrong here. Note that $$frac{partial^2 l(theta, X)}{partial theta^2} $$ is a second derivative, while $$frac{partial l(theta, X)}{partial theta}frac{partial l(theta, X)}{partial theta}^T$$ is a product of two first-order derivatives. As such, they are surely not equal in general: consider for example the function $$l(theta,X) = theta cdot X.$$



          Try reading the wikipedia page on the Fisher information and compare it with your notes.







          share|cite|improve this answer














          share|cite|improve this answer



          share|cite|improve this answer








          edited Nov 21 at 9:51

























          answered Nov 21 at 9:44









          user159517

          4,248930




          4,248930












          • Then what's a lemma that says that they can be equal?
            – mavavilj
            Nov 21 at 9:46










          • @mavavilj I wouldn't look for such a lemma (it would mean that $l$ has to satisfy a certain differential equation for all $X$, which is a very strict limitation), I'd rather try to understand what was meant in your notes. What is the definition of $l$?
            – user159517
            Nov 21 at 9:49










          • The wikipedia says same as my notes: "If log f(x; θ) is twice differentiable with respect to θ, and under certain regularity conditions,[4] then the Fisher information may also be written as". But I want to know what the lemma is that allows for that equality.
            – mavavilj
            Nov 21 at 9:52












          • Cramer-Rao bound? stat.tamu.edu/~suhasini/teaching613/inference.pdf (Theorem 1.1)
            – mavavilj
            Nov 21 at 9:53


















          • Then what's a lemma that says that they can be equal?
            – mavavilj
            Nov 21 at 9:46










          • @mavavilj I wouldn't look for such a lemma (it would mean that $l$ has to satisfy a certain differential equation for all $X$, which is a very strict limitation), I'd rather try to understand what was meant in your notes. What is the definition of $l$?
            – user159517
            Nov 21 at 9:49










          • The wikipedia says same as my notes: "If log f(x; θ) is twice differentiable with respect to θ, and under certain regularity conditions,[4] then the Fisher information may also be written as". But I want to know what the lemma is that allows for that equality.
            – mavavilj
            Nov 21 at 9:52












          • Cramer-Rao bound? stat.tamu.edu/~suhasini/teaching613/inference.pdf (Theorem 1.1)
            – mavavilj
            Nov 21 at 9:53
















          Then what's a lemma that says that they can be equal?
          – mavavilj
          Nov 21 at 9:46




          Then what's a lemma that says that they can be equal?
          – mavavilj
          Nov 21 at 9:46












          @mavavilj I wouldn't look for such a lemma (it would mean that $l$ has to satisfy a certain differential equation for all $X$, which is a very strict limitation), I'd rather try to understand what was meant in your notes. What is the definition of $l$?
          – user159517
          Nov 21 at 9:49




          @mavavilj I wouldn't look for such a lemma (it would mean that $l$ has to satisfy a certain differential equation for all $X$, which is a very strict limitation), I'd rather try to understand what was meant in your notes. What is the definition of $l$?
          – user159517
          Nov 21 at 9:49












          The wikipedia says same as my notes: "If log f(x; θ) is twice differentiable with respect to θ, and under certain regularity conditions,[4] then the Fisher information may also be written as". But I want to know what the lemma is that allows for that equality.
          – mavavilj
          Nov 21 at 9:52






          The wikipedia says same as my notes: "If log f(x; θ) is twice differentiable with respect to θ, and under certain regularity conditions,[4] then the Fisher information may also be written as". But I want to know what the lemma is that allows for that equality.
          – mavavilj
          Nov 21 at 9:52














          Cramer-Rao bound? stat.tamu.edu/~suhasini/teaching613/inference.pdf (Theorem 1.1)
          – mavavilj
          Nov 21 at 9:53




          Cramer-Rao bound? stat.tamu.edu/~suhasini/teaching613/inference.pdf (Theorem 1.1)
          – mavavilj
          Nov 21 at 9:53


















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