(PCA) Effect of holding the sum of squared coefficients to 1












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In principal-component analysis, the variables $x1, x2 ... xp$ are replaced by a more convenient set $u1, u2 ... up$ where the new variables are linear combinations of the old.



enter image description here



To hold the new vectors to the same scale as the original set, the sum of the squared coefficients is fixed to unity:



enter image description here



How exactly does fixing the squared coefficients to 1 maintain the same scale? And why the squared coefficients not the coefficients themselves?










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    0












    $begingroup$


    In principal-component analysis, the variables $x1, x2 ... xp$ are replaced by a more convenient set $u1, u2 ... up$ where the new variables are linear combinations of the old.



    enter image description here



    To hold the new vectors to the same scale as the original set, the sum of the squared coefficients is fixed to unity:



    enter image description here



    How exactly does fixing the squared coefficients to 1 maintain the same scale? And why the squared coefficients not the coefficients themselves?










    share|cite|improve this question









    $endgroup$















      0












      0








      0





      $begingroup$


      In principal-component analysis, the variables $x1, x2 ... xp$ are replaced by a more convenient set $u1, u2 ... up$ where the new variables are linear combinations of the old.



      enter image description here



      To hold the new vectors to the same scale as the original set, the sum of the squared coefficients is fixed to unity:



      enter image description here



      How exactly does fixing the squared coefficients to 1 maintain the same scale? And why the squared coefficients not the coefficients themselves?










      share|cite|improve this question









      $endgroup$




      In principal-component analysis, the variables $x1, x2 ... xp$ are replaced by a more convenient set $u1, u2 ... up$ where the new variables are linear combinations of the old.



      enter image description here



      To hold the new vectors to the same scale as the original set, the sum of the squared coefficients is fixed to unity:



      enter image description here



      How exactly does fixing the squared coefficients to 1 maintain the same scale? And why the squared coefficients not the coefficients themselves?







      linear-algebra






      share|cite|improve this question













      share|cite|improve this question











      share|cite|improve this question




      share|cite|improve this question










      asked Dec 2 '18 at 16:17









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