MAP estimate of Erlang distribution
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I have a hard time approaching this problem. I understand how to find the MAP estimate for common distributions but from the given problem below I have totally confused.
I have a set of $N$ observations that follow the Erlang distribution and the priori probability for the parameter $theta$ is a normal distribution where $theta_o, sigma_0^2$ are known
How can I compute the MAP estimate?
$p(x|theta) = theta^2x e^{-theta x}u(x)~~~mbox{where}~~~u(x)~~~mbox{is}~~~ u(x) = begin{cases}1 & mbox{if}~ x>0\0 & mbox{if}~ x<0 end{cases}$
probability-distributions maximum-likelihood
asked Nov 17 at 22:57
Er1Hall
62
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up vote
0
down vote
favorite
I have a hard time approaching this problem. I understand how to find the MAP estimate for common distributions but from the given problem below I have totally confused.
I have a set of $N$ observations that follow the Erlang distribution and the priori probability for the parameter $theta$ is a normal distribution where $theta_o, sigma_0^2$ are known
How can I compute the MAP estimate?
$p(x|theta) = theta^2x e^{-theta x}u(x)~~~mbox{where}~~~u(x)~~~mbox{is}~~~ u(x) = begin{cases}1 & mbox{if}~ x>0\0 & mbox{if}~ x<0 end{cases}$
probability-distributions maximum-likelihood
asked Nov 17 at 22:57
Er1Hall
62
If you understand how to find the MAP estimate for common distributions then what is it about just repeating the process that is confusing you here? Flesh out your problem a little more to get the most helpful responses
– Nadiels
Nov 17 at 23:02
add a comment |
up vote
0
down vote
favorite
up vote
0
down vote
favorite
I have a hard time approaching this problem. I understand how to find the MAP estimate for common distributions but from the given problem below I have totally confused.
I have a set of $N$ observations that follow the Erlang distribution and the priori probability for the parameter $theta$ is a normal distribution where $theta_o, sigma_0^2$ are known
How can I compute the MAP estimate?
$p(x|theta) = theta^2x e^{-theta x}u(x)~~~mbox{where}~~~u(x)~~~mbox{is}~~~ u(x) = begin{cases}1 & mbox{if}~ x>0\0 & mbox{if}~ x<0 end{cases}$
probability-distributions maximum-likelihood
asked Nov 17 at 22:57
Er1Hall
62
I have a hard time approaching this problem. I understand how to find the MAP estimate for common distributions but from the given problem below I have totally confused.
I have a set of $N$ observations that follow the Erlang distribution and the priori probability for the parameter $theta$ is a normal distribution where $theta_o, sigma_0^2$ are known
How can I compute the MAP estimate?
$p(x|theta) = theta^2x e^{-theta x}u(x)~~~mbox{where}~~~u(x)~~~mbox{is}~~~ u(x) = begin{cases}1 & mbox{if}~ x>0\0 & mbox{if}~ x<0 end{cases}$
probability-distributions maximum-likelihood
probability-distributions maximum-likelihood
asked Nov 17 at 22:57
Er1Hall
62
asked Nov 17 at 22:57
Er1Hall
62
asked Nov 17 at 22:57
Er1Hall
62
asked Nov 17 at 22:57
Er1Hall
62
asked Nov 17 at 22:57
Er1Hall
62
62
If you understand how to find the MAP estimate for common distributions then what is it about just repeating the process that is confusing you here? Flesh out your problem a little more to get the most helpful responses
– Nadiels
Nov 17 at 23:02
add a comment |
If you understand how to find the MAP estimate for common distributions then what is it about just repeating the process that is confusing you here? Flesh out your problem a little more to get the most helpful responses
– Nadiels
Nov 17 at 23:02
If you understand how to find the MAP estimate for common distributions then what is it about just repeating the process that is confusing you here? Flesh out your problem a little more to get the most helpful responses
– Nadiels
Nov 17 at 23:02
If you understand how to find the MAP estimate for common distributions then what is it about just repeating the process that is confusing you here? Flesh out your problem a little more to get the most helpful responses
– Nadiels
Nov 17 at 23:02
add a comment |
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If you understand how to find the MAP estimate for common distributions then what is it about just repeating the process that is confusing you here? Flesh out your problem a little more to get the most helpful responses
– Nadiels
Nov 17 at 23:02