L1 as Probability space











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In a continuous optimization problem, I consider the functions belonging to the "space of probabilities" on $lbrack 0,1 rbrack^N $ that admit a probability density. I understand that I exclude in the process distributions such as the Dirac.



Can I use a subset of the Lebesgue $L_1(lbrack 0,1 rbrack^N) $ space for that matter?
To be specific, can I use :
$$ { p in L_1 | int p = 1, pgeq0 } $$










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  • Yes,you can. This identification is useful in many ways.
    – Kavi Rama Murthy
    Nov 20 at 8:53










  • This is not fully accurate. What is the underlying space of $L_1$? What measure are integrating the function $p$ against?
    – uniquesolution
    Nov 20 at 9:04










  • Thanks both of you for your answers. $L_1$ is defined on $lbrack 0, 1 rbrack^N$ where N is an integer, and the measure is the Lebesgue measure. I will edit the question.
    – Mathieu
    Nov 20 at 9:45















up vote
0
down vote

favorite












In a continuous optimization problem, I consider the functions belonging to the "space of probabilities" on $lbrack 0,1 rbrack^N $ that admit a probability density. I understand that I exclude in the process distributions such as the Dirac.



Can I use a subset of the Lebesgue $L_1(lbrack 0,1 rbrack^N) $ space for that matter?
To be specific, can I use :
$$ { p in L_1 | int p = 1, pgeq0 } $$










share|cite|improve this question
























  • Yes,you can. This identification is useful in many ways.
    – Kavi Rama Murthy
    Nov 20 at 8:53










  • This is not fully accurate. What is the underlying space of $L_1$? What measure are integrating the function $p$ against?
    – uniquesolution
    Nov 20 at 9:04










  • Thanks both of you for your answers. $L_1$ is defined on $lbrack 0, 1 rbrack^N$ where N is an integer, and the measure is the Lebesgue measure. I will edit the question.
    – Mathieu
    Nov 20 at 9:45













up vote
0
down vote

favorite









up vote
0
down vote

favorite











In a continuous optimization problem, I consider the functions belonging to the "space of probabilities" on $lbrack 0,1 rbrack^N $ that admit a probability density. I understand that I exclude in the process distributions such as the Dirac.



Can I use a subset of the Lebesgue $L_1(lbrack 0,1 rbrack^N) $ space for that matter?
To be specific, can I use :
$$ { p in L_1 | int p = 1, pgeq0 } $$










share|cite|improve this question















In a continuous optimization problem, I consider the functions belonging to the "space of probabilities" on $lbrack 0,1 rbrack^N $ that admit a probability density. I understand that I exclude in the process distributions such as the Dirac.



Can I use a subset of the Lebesgue $L_1(lbrack 0,1 rbrack^N) $ space for that matter?
To be specific, can I use :
$$ { p in L_1 | int p = 1, pgeq0 } $$







probability probability-theory probability-distributions






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share|cite|improve this question













share|cite|improve this question




share|cite|improve this question








edited Nov 20 at 9:53

























asked Nov 20 at 8:51









Mathieu

12




12












  • Yes,you can. This identification is useful in many ways.
    – Kavi Rama Murthy
    Nov 20 at 8:53










  • This is not fully accurate. What is the underlying space of $L_1$? What measure are integrating the function $p$ against?
    – uniquesolution
    Nov 20 at 9:04










  • Thanks both of you for your answers. $L_1$ is defined on $lbrack 0, 1 rbrack^N$ where N is an integer, and the measure is the Lebesgue measure. I will edit the question.
    – Mathieu
    Nov 20 at 9:45


















  • Yes,you can. This identification is useful in many ways.
    – Kavi Rama Murthy
    Nov 20 at 8:53










  • This is not fully accurate. What is the underlying space of $L_1$? What measure are integrating the function $p$ against?
    – uniquesolution
    Nov 20 at 9:04










  • Thanks both of you for your answers. $L_1$ is defined on $lbrack 0, 1 rbrack^N$ where N is an integer, and the measure is the Lebesgue measure. I will edit the question.
    – Mathieu
    Nov 20 at 9:45
















Yes,you can. This identification is useful in many ways.
– Kavi Rama Murthy
Nov 20 at 8:53




Yes,you can. This identification is useful in many ways.
– Kavi Rama Murthy
Nov 20 at 8:53












This is not fully accurate. What is the underlying space of $L_1$? What measure are integrating the function $p$ against?
– uniquesolution
Nov 20 at 9:04




This is not fully accurate. What is the underlying space of $L_1$? What measure are integrating the function $p$ against?
– uniquesolution
Nov 20 at 9:04












Thanks both of you for your answers. $L_1$ is defined on $lbrack 0, 1 rbrack^N$ where N is an integer, and the measure is the Lebesgue measure. I will edit the question.
– Mathieu
Nov 20 at 9:45




Thanks both of you for your answers. $L_1$ is defined on $lbrack 0, 1 rbrack^N$ where N is an integer, and the measure is the Lebesgue measure. I will edit the question.
– Mathieu
Nov 20 at 9:45















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