Eigen-decomposition of real Symmetric psd matrix












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I am doing PCA analysis on a large amount of data and I need to compute the eigen-decomposition of the covariance matrix which is a real, symmetric, positive semi definite matrix. It doesn't get any simpler than that!



I want to compute this myself from first principles and not using some matlab, mathematica or whatever package. That's an infinite process but I am looking for a fast and robust method. Can anyone post an algorithm for it? I did a web search and found several methods but nothing complete and from scratch.



Please help, thanks in advance.










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  • $begingroup$
    You will find answer to it and many others in a best seller, very often cited in scientific papers: "Matrix Computations" by Golub and Van Loan. I know that listing books may lead to an endless dangerous chat, but this book is special ...
    $endgroup$
    – Damien
    Dec 4 '18 at 9:29






  • 1




    $begingroup$
    I want to reinvent a wheel but have no idea what a wheel looks like, can you post one? I'm impressed by your resolute denial of computer codes people worked on for decades, sir.
    $endgroup$
    – Algebraic Pavel
    Dec 4 '18 at 9:40










  • $begingroup$
    @AlgebraicPavel Sometimes, when you are doing research, you are not only interested in the functionality of a program, but you want to deeply understand it. And sometimes, the benefit of such a deep understanding of a given function appear a long time after, in an unexpected way.
    $endgroup$
    – Damien
    Dec 4 '18 at 10:02










  • $begingroup$
    @Damien I understand that what you say might be happening but the question does not give me an impression that this is the case.
    $endgroup$
    – Algebraic Pavel
    Dec 4 '18 at 10:55










  • $begingroup$
    @Damien Thanks! It's quite involved with bidiagonal matrices and so on but it looks like I can't do any better...
    $endgroup$
    – plus1
    Dec 4 '18 at 11:10
















0












$begingroup$


I am doing PCA analysis on a large amount of data and I need to compute the eigen-decomposition of the covariance matrix which is a real, symmetric, positive semi definite matrix. It doesn't get any simpler than that!



I want to compute this myself from first principles and not using some matlab, mathematica or whatever package. That's an infinite process but I am looking for a fast and robust method. Can anyone post an algorithm for it? I did a web search and found several methods but nothing complete and from scratch.



Please help, thanks in advance.










share|cite|improve this question









$endgroup$












  • $begingroup$
    You will find answer to it and many others in a best seller, very often cited in scientific papers: "Matrix Computations" by Golub and Van Loan. I know that listing books may lead to an endless dangerous chat, but this book is special ...
    $endgroup$
    – Damien
    Dec 4 '18 at 9:29






  • 1




    $begingroup$
    I want to reinvent a wheel but have no idea what a wheel looks like, can you post one? I'm impressed by your resolute denial of computer codes people worked on for decades, sir.
    $endgroup$
    – Algebraic Pavel
    Dec 4 '18 at 9:40










  • $begingroup$
    @AlgebraicPavel Sometimes, when you are doing research, you are not only interested in the functionality of a program, but you want to deeply understand it. And sometimes, the benefit of such a deep understanding of a given function appear a long time after, in an unexpected way.
    $endgroup$
    – Damien
    Dec 4 '18 at 10:02










  • $begingroup$
    @Damien I understand that what you say might be happening but the question does not give me an impression that this is the case.
    $endgroup$
    – Algebraic Pavel
    Dec 4 '18 at 10:55










  • $begingroup$
    @Damien Thanks! It's quite involved with bidiagonal matrices and so on but it looks like I can't do any better...
    $endgroup$
    – plus1
    Dec 4 '18 at 11:10














0












0








0





$begingroup$


I am doing PCA analysis on a large amount of data and I need to compute the eigen-decomposition of the covariance matrix which is a real, symmetric, positive semi definite matrix. It doesn't get any simpler than that!



I want to compute this myself from first principles and not using some matlab, mathematica or whatever package. That's an infinite process but I am looking for a fast and robust method. Can anyone post an algorithm for it? I did a web search and found several methods but nothing complete and from scratch.



Please help, thanks in advance.










share|cite|improve this question









$endgroup$




I am doing PCA analysis on a large amount of data and I need to compute the eigen-decomposition of the covariance matrix which is a real, symmetric, positive semi definite matrix. It doesn't get any simpler than that!



I want to compute this myself from first principles and not using some matlab, mathematica or whatever package. That's an infinite process but I am looking for a fast and robust method. Can anyone post an algorithm for it? I did a web search and found several methods but nothing complete and from scratch.



Please help, thanks in advance.







linear-algebra matrices eigenvalues-eigenvectors linear-transformations singularvalues






share|cite|improve this question













share|cite|improve this question











share|cite|improve this question




share|cite|improve this question










asked Dec 4 '18 at 9:17









plus1plus1

4111




4111












  • $begingroup$
    You will find answer to it and many others in a best seller, very often cited in scientific papers: "Matrix Computations" by Golub and Van Loan. I know that listing books may lead to an endless dangerous chat, but this book is special ...
    $endgroup$
    – Damien
    Dec 4 '18 at 9:29






  • 1




    $begingroup$
    I want to reinvent a wheel but have no idea what a wheel looks like, can you post one? I'm impressed by your resolute denial of computer codes people worked on for decades, sir.
    $endgroup$
    – Algebraic Pavel
    Dec 4 '18 at 9:40










  • $begingroup$
    @AlgebraicPavel Sometimes, when you are doing research, you are not only interested in the functionality of a program, but you want to deeply understand it. And sometimes, the benefit of such a deep understanding of a given function appear a long time after, in an unexpected way.
    $endgroup$
    – Damien
    Dec 4 '18 at 10:02










  • $begingroup$
    @Damien I understand that what you say might be happening but the question does not give me an impression that this is the case.
    $endgroup$
    – Algebraic Pavel
    Dec 4 '18 at 10:55










  • $begingroup$
    @Damien Thanks! It's quite involved with bidiagonal matrices and so on but it looks like I can't do any better...
    $endgroup$
    – plus1
    Dec 4 '18 at 11:10


















  • $begingroup$
    You will find answer to it and many others in a best seller, very often cited in scientific papers: "Matrix Computations" by Golub and Van Loan. I know that listing books may lead to an endless dangerous chat, but this book is special ...
    $endgroup$
    – Damien
    Dec 4 '18 at 9:29






  • 1




    $begingroup$
    I want to reinvent a wheel but have no idea what a wheel looks like, can you post one? I'm impressed by your resolute denial of computer codes people worked on for decades, sir.
    $endgroup$
    – Algebraic Pavel
    Dec 4 '18 at 9:40










  • $begingroup$
    @AlgebraicPavel Sometimes, when you are doing research, you are not only interested in the functionality of a program, but you want to deeply understand it. And sometimes, the benefit of such a deep understanding of a given function appear a long time after, in an unexpected way.
    $endgroup$
    – Damien
    Dec 4 '18 at 10:02










  • $begingroup$
    @Damien I understand that what you say might be happening but the question does not give me an impression that this is the case.
    $endgroup$
    – Algebraic Pavel
    Dec 4 '18 at 10:55










  • $begingroup$
    @Damien Thanks! It's quite involved with bidiagonal matrices and so on but it looks like I can't do any better...
    $endgroup$
    – plus1
    Dec 4 '18 at 11:10
















$begingroup$
You will find answer to it and many others in a best seller, very often cited in scientific papers: "Matrix Computations" by Golub and Van Loan. I know that listing books may lead to an endless dangerous chat, but this book is special ...
$endgroup$
– Damien
Dec 4 '18 at 9:29




$begingroup$
You will find answer to it and many others in a best seller, very often cited in scientific papers: "Matrix Computations" by Golub and Van Loan. I know that listing books may lead to an endless dangerous chat, but this book is special ...
$endgroup$
– Damien
Dec 4 '18 at 9:29




1




1




$begingroup$
I want to reinvent a wheel but have no idea what a wheel looks like, can you post one? I'm impressed by your resolute denial of computer codes people worked on for decades, sir.
$endgroup$
– Algebraic Pavel
Dec 4 '18 at 9:40




$begingroup$
I want to reinvent a wheel but have no idea what a wheel looks like, can you post one? I'm impressed by your resolute denial of computer codes people worked on for decades, sir.
$endgroup$
– Algebraic Pavel
Dec 4 '18 at 9:40












$begingroup$
@AlgebraicPavel Sometimes, when you are doing research, you are not only interested in the functionality of a program, but you want to deeply understand it. And sometimes, the benefit of such a deep understanding of a given function appear a long time after, in an unexpected way.
$endgroup$
– Damien
Dec 4 '18 at 10:02




$begingroup$
@AlgebraicPavel Sometimes, when you are doing research, you are not only interested in the functionality of a program, but you want to deeply understand it. And sometimes, the benefit of such a deep understanding of a given function appear a long time after, in an unexpected way.
$endgroup$
– Damien
Dec 4 '18 at 10:02












$begingroup$
@Damien I understand that what you say might be happening but the question does not give me an impression that this is the case.
$endgroup$
– Algebraic Pavel
Dec 4 '18 at 10:55




$begingroup$
@Damien I understand that what you say might be happening but the question does not give me an impression that this is the case.
$endgroup$
– Algebraic Pavel
Dec 4 '18 at 10:55












$begingroup$
@Damien Thanks! It's quite involved with bidiagonal matrices and so on but it looks like I can't do any better...
$endgroup$
– plus1
Dec 4 '18 at 11:10




$begingroup$
@Damien Thanks! It's quite involved with bidiagonal matrices and so on but it looks like I can't do any better...
$endgroup$
– plus1
Dec 4 '18 at 11:10










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