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Help with understanding a procedure in probability
Help with understanding and studying probabilityUnderstanding Chebyshev's Theoremhelp understanding probabilityWhat is the variance of an arbitrary “good” function of several independent normally distributed random variablesAn equality from the well-known analysis of variance formulaBiased estimator of the Variance of a Gaussian DistributionFinding stationary distribution of the following stochastic process?A probability question - help with understandingTransformation of random variables in entropy termBishop - Pattern Recognition & Machine Learning, Exercise 1.4
$begingroup$
I'm reading a book but I probably don't remember all the math needed to solve this.
The book says that:
x, y are two random variables such that y=g(x) where g is an invertible, continuous and differentiable transformation.
We have this property:
$|p_y(g(x))dy| = |p_x(x)dx|$ (1)
And solving from the equation you obtain:
$p_y(y)=p_x(g^-1(y))left|dfracpartial xpartial y right| $ (2)
or equivalently
$p_x(x)=p_y(g(x))left|dfracpartial g(x)partial x right|$ (3)
Passing from (1) to (2) I'm not sure how to deal with the differentials.
And passing from (2) to (3) i'm almost completely lost.
Can you please help me?
probability
$endgroup$
add a comment |
$begingroup$
I'm reading a book but I probably don't remember all the math needed to solve this.
The book says that:
x, y are two random variables such that y=g(x) where g is an invertible, continuous and differentiable transformation.
We have this property:
$|p_y(g(x))dy| = |p_x(x)dx|$ (1)
And solving from the equation you obtain:
$p_y(y)=p_x(g^-1(y))left|dfracpartial xpartial y right| $ (2)
or equivalently
$p_x(x)=p_y(g(x))left|dfracpartial g(x)partial x right|$ (3)
Passing from (1) to (2) I'm not sure how to deal with the differentials.
And passing from (2) to (3) i'm almost completely lost.
Can you please help me?
probability
$endgroup$
add a comment |
$begingroup$
I'm reading a book but I probably don't remember all the math needed to solve this.
The book says that:
x, y are two random variables such that y=g(x) where g is an invertible, continuous and differentiable transformation.
We have this property:
$|p_y(g(x))dy| = |p_x(x)dx|$ (1)
And solving from the equation you obtain:
$p_y(y)=p_x(g^-1(y))left|dfracpartial xpartial y right| $ (2)
or equivalently
$p_x(x)=p_y(g(x))left|dfracpartial g(x)partial x right|$ (3)
Passing from (1) to (2) I'm not sure how to deal with the differentials.
And passing from (2) to (3) i'm almost completely lost.
Can you please help me?
probability
$endgroup$
I'm reading a book but I probably don't remember all the math needed to solve this.
The book says that:
x, y are two random variables such that y=g(x) where g is an invertible, continuous and differentiable transformation.
We have this property:
$|p_y(g(x))dy| = |p_x(x)dx|$ (1)
And solving from the equation you obtain:
$p_y(y)=p_x(g^-1(y))left|dfracpartial xpartial y right| $ (2)
or equivalently
$p_x(x)=p_y(g(x))left|dfracpartial g(x)partial x right|$ (3)
Passing from (1) to (2) I'm not sure how to deal with the differentials.
And passing from (2) to (3) i'm almost completely lost.
Can you please help me?
probability
probability
asked Mar 21 at 12:49
Diego MoyaDiego Moya
11
11
add a comment |
add a comment |
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