predicting random walks with eigenvalues The Next CEO of Stack OverflowEigenvalue & Eigenvector questionSimple Probability MatrixProbability Markov chain, system of equationsIs there a function in MATLAB that will estimate the initial condition from a set of data?Compute power of a matrix $A$ as $nrightarrow infty$Expected time to reach final state for a random walk on a finite gridDynamical Systems with EigenvectorsAverage distance between consecutive points in a one-dimensional auto-correlated sequenceRandom walks with “bumping” particlesRandom walks with recurrence

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predicting random walks with eigenvalues



The Next CEO of Stack OverflowEigenvalue & Eigenvector questionSimple Probability MatrixProbability Markov chain, system of equationsIs there a function in MATLAB that will estimate the initial condition from a set of data?Compute power of a matrix $A$ as $nrightarrow infty$Expected time to reach final state for a random walk on a finite gridDynamical Systems with EigenvectorsAverage distance between consecutive points in a one-dimensional auto-correlated sequenceRandom walks with “bumping” particlesRandom walks with recurrence










0












$begingroup$


(1 point) Consider a simple model that predicts whether you pass your next test or not based on the result of your previous test.



If you pass your previous test, then you have 0.6 chance you will pass your upcoming test.
If you fail your previous test, then you have 0.2 change you will fail your upcoming test.
If it continues over a long time, what is the probability that you will pass a test?



I know that I should use eigenvector = 1 and the relationship Ax=A.



I have the matrix [ 0.6 , 0.4],[0.2,0.8]



If I subtract lambda=1 along the diagonal I get,



[-0.4,0.4][0.2,-0.8]*[ Pass, Fail] = [pass, fail]



How do I find the [pass,fail] vector?










share|cite|improve this question









$endgroup$
















    0












    $begingroup$


    (1 point) Consider a simple model that predicts whether you pass your next test or not based on the result of your previous test.



    If you pass your previous test, then you have 0.6 chance you will pass your upcoming test.
    If you fail your previous test, then you have 0.2 change you will fail your upcoming test.
    If it continues over a long time, what is the probability that you will pass a test?



    I know that I should use eigenvector = 1 and the relationship Ax=A.



    I have the matrix [ 0.6 , 0.4],[0.2,0.8]



    If I subtract lambda=1 along the diagonal I get,



    [-0.4,0.4][0.2,-0.8]*[ Pass, Fail] = [pass, fail]



    How do I find the [pass,fail] vector?










    share|cite|improve this question









    $endgroup$














      0












      0








      0





      $begingroup$


      (1 point) Consider a simple model that predicts whether you pass your next test or not based on the result of your previous test.



      If you pass your previous test, then you have 0.6 chance you will pass your upcoming test.
      If you fail your previous test, then you have 0.2 change you will fail your upcoming test.
      If it continues over a long time, what is the probability that you will pass a test?



      I know that I should use eigenvector = 1 and the relationship Ax=A.



      I have the matrix [ 0.6 , 0.4],[0.2,0.8]



      If I subtract lambda=1 along the diagonal I get,



      [-0.4,0.4][0.2,-0.8]*[ Pass, Fail] = [pass, fail]



      How do I find the [pass,fail] vector?










      share|cite|improve this question









      $endgroup$




      (1 point) Consider a simple model that predicts whether you pass your next test or not based on the result of your previous test.



      If you pass your previous test, then you have 0.6 chance you will pass your upcoming test.
      If you fail your previous test, then you have 0.2 change you will fail your upcoming test.
      If it continues over a long time, what is the probability that you will pass a test?



      I know that I should use eigenvector = 1 and the relationship Ax=A.



      I have the matrix [ 0.6 , 0.4],[0.2,0.8]



      If I subtract lambda=1 along the diagonal I get,



      [-0.4,0.4][0.2,-0.8]*[ Pass, Fail] = [pass, fail]



      How do I find the [pass,fail] vector?







      linear-algebra random-walk






      share|cite|improve this question













      share|cite|improve this question











      share|cite|improve this question




      share|cite|improve this question










      asked Mar 28 at 3:54









      MCCMCC

      316




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