Density function of conditional random variable without knowing joint distrbution.












1












$begingroup$


I have Z and X which are two random variables with density:



$f_Z(z) = 3(1-z)^2mathbb{1}_{[0,1]}(z)$



$f_X(x) = 6x(1-x)mathbb{1}_{[0,1]}(x)$



I want to find $f_{Z vert X = x}(z)$, but to do that I have to calculate the joint density which is unknown. (The two random variables are not independent). Is there another way? If not, how do I calculate the joint density?



EDIT: The random variable Z was defined as: $$ Z = XU $$ with $f_U(u) = mathbb{1}_{[0,1]}(u)$










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$endgroup$








  • 1




    $begingroup$
    Without knowing anything about the dependence, it doesn't seem that there is enough information to solve the problem.
    $endgroup$
    – Greg Martin
    Jan 15 at 20:12










  • $begingroup$
    @GregMartin I see, I will edit and add more information.
    $endgroup$
    – qcc101
    Jan 15 at 20:16






  • 1




    $begingroup$
    Again you have to tell us the relationship between $X$ and $U$, otherwise we cannot be certain. Assume you means they are independent. Then the question is easy - you do not need to do any tedious derivation - the conditional distribution of $Z$ given $X = x$ is simply $xU sim text{Uniform}(0, x)$.
    $endgroup$
    – BGM
    Jan 16 at 3:23










  • $begingroup$
    Yes sorry about that, they indeed are independent.
    $endgroup$
    – qcc101
    Jan 16 at 6:31
















1












$begingroup$


I have Z and X which are two random variables with density:



$f_Z(z) = 3(1-z)^2mathbb{1}_{[0,1]}(z)$



$f_X(x) = 6x(1-x)mathbb{1}_{[0,1]}(x)$



I want to find $f_{Z vert X = x}(z)$, but to do that I have to calculate the joint density which is unknown. (The two random variables are not independent). Is there another way? If not, how do I calculate the joint density?



EDIT: The random variable Z was defined as: $$ Z = XU $$ with $f_U(u) = mathbb{1}_{[0,1]}(u)$










share|cite|improve this question











$endgroup$








  • 1




    $begingroup$
    Without knowing anything about the dependence, it doesn't seem that there is enough information to solve the problem.
    $endgroup$
    – Greg Martin
    Jan 15 at 20:12










  • $begingroup$
    @GregMartin I see, I will edit and add more information.
    $endgroup$
    – qcc101
    Jan 15 at 20:16






  • 1




    $begingroup$
    Again you have to tell us the relationship between $X$ and $U$, otherwise we cannot be certain. Assume you means they are independent. Then the question is easy - you do not need to do any tedious derivation - the conditional distribution of $Z$ given $X = x$ is simply $xU sim text{Uniform}(0, x)$.
    $endgroup$
    – BGM
    Jan 16 at 3:23










  • $begingroup$
    Yes sorry about that, they indeed are independent.
    $endgroup$
    – qcc101
    Jan 16 at 6:31














1












1








1





$begingroup$


I have Z and X which are two random variables with density:



$f_Z(z) = 3(1-z)^2mathbb{1}_{[0,1]}(z)$



$f_X(x) = 6x(1-x)mathbb{1}_{[0,1]}(x)$



I want to find $f_{Z vert X = x}(z)$, but to do that I have to calculate the joint density which is unknown. (The two random variables are not independent). Is there another way? If not, how do I calculate the joint density?



EDIT: The random variable Z was defined as: $$ Z = XU $$ with $f_U(u) = mathbb{1}_{[0,1]}(u)$










share|cite|improve this question











$endgroup$




I have Z and X which are two random variables with density:



$f_Z(z) = 3(1-z)^2mathbb{1}_{[0,1]}(z)$



$f_X(x) = 6x(1-x)mathbb{1}_{[0,1]}(x)$



I want to find $f_{Z vert X = x}(z)$, but to do that I have to calculate the joint density which is unknown. (The two random variables are not independent). Is there another way? If not, how do I calculate the joint density?



EDIT: The random variable Z was defined as: $$ Z = XU $$ with $f_U(u) = mathbb{1}_{[0,1]}(u)$







probability conditional-expectation






share|cite|improve this question















share|cite|improve this question













share|cite|improve this question




share|cite|improve this question








edited Jan 15 at 20:18







qcc101

















asked Jan 15 at 19:59









qcc101qcc101

629213




629213








  • 1




    $begingroup$
    Without knowing anything about the dependence, it doesn't seem that there is enough information to solve the problem.
    $endgroup$
    – Greg Martin
    Jan 15 at 20:12










  • $begingroup$
    @GregMartin I see, I will edit and add more information.
    $endgroup$
    – qcc101
    Jan 15 at 20:16






  • 1




    $begingroup$
    Again you have to tell us the relationship between $X$ and $U$, otherwise we cannot be certain. Assume you means they are independent. Then the question is easy - you do not need to do any tedious derivation - the conditional distribution of $Z$ given $X = x$ is simply $xU sim text{Uniform}(0, x)$.
    $endgroup$
    – BGM
    Jan 16 at 3:23










  • $begingroup$
    Yes sorry about that, they indeed are independent.
    $endgroup$
    – qcc101
    Jan 16 at 6:31














  • 1




    $begingroup$
    Without knowing anything about the dependence, it doesn't seem that there is enough information to solve the problem.
    $endgroup$
    – Greg Martin
    Jan 15 at 20:12










  • $begingroup$
    @GregMartin I see, I will edit and add more information.
    $endgroup$
    – qcc101
    Jan 15 at 20:16






  • 1




    $begingroup$
    Again you have to tell us the relationship between $X$ and $U$, otherwise we cannot be certain. Assume you means they are independent. Then the question is easy - you do not need to do any tedious derivation - the conditional distribution of $Z$ given $X = x$ is simply $xU sim text{Uniform}(0, x)$.
    $endgroup$
    – BGM
    Jan 16 at 3:23










  • $begingroup$
    Yes sorry about that, they indeed are independent.
    $endgroup$
    – qcc101
    Jan 16 at 6:31








1




1




$begingroup$
Without knowing anything about the dependence, it doesn't seem that there is enough information to solve the problem.
$endgroup$
– Greg Martin
Jan 15 at 20:12




$begingroup$
Without knowing anything about the dependence, it doesn't seem that there is enough information to solve the problem.
$endgroup$
– Greg Martin
Jan 15 at 20:12












$begingroup$
@GregMartin I see, I will edit and add more information.
$endgroup$
– qcc101
Jan 15 at 20:16




$begingroup$
@GregMartin I see, I will edit and add more information.
$endgroup$
– qcc101
Jan 15 at 20:16




1




1




$begingroup$
Again you have to tell us the relationship between $X$ and $U$, otherwise we cannot be certain. Assume you means they are independent. Then the question is easy - you do not need to do any tedious derivation - the conditional distribution of $Z$ given $X = x$ is simply $xU sim text{Uniform}(0, x)$.
$endgroup$
– BGM
Jan 16 at 3:23




$begingroup$
Again you have to tell us the relationship between $X$ and $U$, otherwise we cannot be certain. Assume you means they are independent. Then the question is easy - you do not need to do any tedious derivation - the conditional distribution of $Z$ given $X = x$ is simply $xU sim text{Uniform}(0, x)$.
$endgroup$
– BGM
Jan 16 at 3:23












$begingroup$
Yes sorry about that, they indeed are independent.
$endgroup$
– qcc101
Jan 16 at 6:31




$begingroup$
Yes sorry about that, they indeed are independent.
$endgroup$
– qcc101
Jan 16 at 6:31










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