How to select a small amount of numbers such that a distribution matches another as closely as possible?












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I have two sets of numbers (1000 in each set, integers), one of those distributions remains constant (reference), but the other changes slightly and some numbers are dropped. When a number is dropped, I need to replace it with another number such that the resulting distribution is as close to the original (reference) as possible.



I could loop over possible values (or combinations in cases where multiple numbers were dropped) and in each iteration perform a KS test and pick the best result, but I was wondering if there may be quicker, more intelligent, ways to go around this.



Thank you in advance!






matlab distribution-theory







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    $begingroup$


    I have two sets of numbers (1000 in each set, integers), one of those distributions remains constant (reference), but the other changes slightly and some numbers are dropped. When a number is dropped, I need to replace it with another number such that the resulting distribution is as close to the original (reference) as possible.



    I could loop over possible values (or combinations in cases where multiple numbers were dropped) and in each iteration perform a KS test and pick the best result, but I was wondering if there may be quicker, more intelligent, ways to go around this.



    Thank you in advance!






    matlab distribution-theory







    share|cite|improve this question









    $endgroup$















      1












      1








      1





      $begingroup$


      I have two sets of numbers (1000 in each set, integers), one of those distributions remains constant (reference), but the other changes slightly and some numbers are dropped. When a number is dropped, I need to replace it with another number such that the resulting distribution is as close to the original (reference) as possible.



      I could loop over possible values (or combinations in cases where multiple numbers were dropped) and in each iteration perform a KS test and pick the best result, but I was wondering if there may be quicker, more intelligent, ways to go around this.



      Thank you in advance!






      matlab distribution-theory







      share|cite|improve this question









      $endgroup$




      I have two sets of numbers (1000 in each set, integers), one of those distributions remains constant (reference), but the other changes slightly and some numbers are dropped. When a number is dropped, I need to replace it with another number such that the resulting distribution is as close to the original (reference) as possible.



      I could loop over possible values (or combinations in cases where multiple numbers were dropped) and in each iteration perform a KS test and pick the best result, but I was wondering if there may be quicker, more intelligent, ways to go around this.



      Thank you in advance!






      matlab distribution-theory




      matlab distribution-theory






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      share|cite|improve this question











      share|cite|improve this question




      share|cite|improve this question










      asked Feb 2 at 23:47









      MrKaplanMrKaplan

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