Mixing
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
asked Feb 2 at 23:47
MrKaplanMrKaplan
83
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add a comment |
$begingroup$
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
asked Feb 2 at 23:47
MrKaplanMrKaplan
83
$endgroup$
add a comment |
$begingroup$
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
asked Feb 2 at 23:47
MrKaplanMrKaplan
83
$endgroup$
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
asked Feb 2 at 23:47
MrKaplanMrKaplan
83
asked Feb 2 at 23:47
MrKaplanMrKaplan
83
asked Feb 2 at 23:47
MrKaplanMrKaplan
83
asked Feb 2 at 23:47
MrKaplanMrKaplan
83
asked Feb 2 at 23:47
MrKaplanMrKaplan
83
83
add a comment |
add a comment |
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