Confusion about notation on continuous pathed stochastic processes
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In the definition below, I am unsure on what the $[omega]$ in $X(t)[omega]$ is meant to signify.
Is it saying that we first observe a stochastic process, create the mapping with the seen values of the random variables, then we denote values of the random variables by $X(t)[omega]$?
stochastic-processes
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add a comment |
$begingroup$
In the definition below, I am unsure on what the $[omega]$ in $X(t)[omega]$ is meant to signify.
Is it saying that we first observe a stochastic process, create the mapping with the seen values of the random variables, then we denote values of the random variables by $X(t)[omega]$?
stochastic-processes
$endgroup$
add a comment |
$begingroup$
In the definition below, I am unsure on what the $[omega]$ in $X(t)[omega]$ is meant to signify.
Is it saying that we first observe a stochastic process, create the mapping with the seen values of the random variables, then we denote values of the random variables by $X(t)[omega]$?
stochastic-processes
$endgroup$
In the definition below, I am unsure on what the $[omega]$ in $X(t)[omega]$ is meant to signify.
Is it saying that we first observe a stochastic process, create the mapping with the seen values of the random variables, then we denote values of the random variables by $X(t)[omega]$?
stochastic-processes
stochastic-processes
asked Jan 1 at 23:57
DLBDLB
548
548
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1 Answer
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$begingroup$
Your stochastic process ${X(t),tgeq0}$ is defined on some underlying set $Omega$ (which we don't make reference to very often). This way, for each $tgeq0$, $X(t)$ is a function $$X(t):Omegatomathbb{R}.$$ $omega$ is just a generic element of the underlying space $Omega$. Thus for each $tgeq0$ and $omegainOmega$, $X(t)(omega)$ is a real number. By fixing $omegainOmega$ we can think of the mapping $$tmapsto X(t)(omega)$$ as a real-valued function over time.
The definition provided is just saying that the set of all $omegainOmega$ for which the above mapping is continuous is required to have probability measure 1.
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1 Answer
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active
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1 Answer
1
active
oldest
votes
active
oldest
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active
oldest
votes
$begingroup$
Your stochastic process ${X(t),tgeq0}$ is defined on some underlying set $Omega$ (which we don't make reference to very often). This way, for each $tgeq0$, $X(t)$ is a function $$X(t):Omegatomathbb{R}.$$ $omega$ is just a generic element of the underlying space $Omega$. Thus for each $tgeq0$ and $omegainOmega$, $X(t)(omega)$ is a real number. By fixing $omegainOmega$ we can think of the mapping $$tmapsto X(t)(omega)$$ as a real-valued function over time.
The definition provided is just saying that the set of all $omegainOmega$ for which the above mapping is continuous is required to have probability measure 1.
$endgroup$
add a comment |
$begingroup$
Your stochastic process ${X(t),tgeq0}$ is defined on some underlying set $Omega$ (which we don't make reference to very often). This way, for each $tgeq0$, $X(t)$ is a function $$X(t):Omegatomathbb{R}.$$ $omega$ is just a generic element of the underlying space $Omega$. Thus for each $tgeq0$ and $omegainOmega$, $X(t)(omega)$ is a real number. By fixing $omegainOmega$ we can think of the mapping $$tmapsto X(t)(omega)$$ as a real-valued function over time.
The definition provided is just saying that the set of all $omegainOmega$ for which the above mapping is continuous is required to have probability measure 1.
$endgroup$
add a comment |
$begingroup$
Your stochastic process ${X(t),tgeq0}$ is defined on some underlying set $Omega$ (which we don't make reference to very often). This way, for each $tgeq0$, $X(t)$ is a function $$X(t):Omegatomathbb{R}.$$ $omega$ is just a generic element of the underlying space $Omega$. Thus for each $tgeq0$ and $omegainOmega$, $X(t)(omega)$ is a real number. By fixing $omegainOmega$ we can think of the mapping $$tmapsto X(t)(omega)$$ as a real-valued function over time.
The definition provided is just saying that the set of all $omegainOmega$ for which the above mapping is continuous is required to have probability measure 1.
$endgroup$
Your stochastic process ${X(t),tgeq0}$ is defined on some underlying set $Omega$ (which we don't make reference to very often). This way, for each $tgeq0$, $X(t)$ is a function $$X(t):Omegatomathbb{R}.$$ $omega$ is just a generic element of the underlying space $Omega$. Thus for each $tgeq0$ and $omegainOmega$, $X(t)(omega)$ is a real number. By fixing $omegainOmega$ we can think of the mapping $$tmapsto X(t)(omega)$$ as a real-valued function over time.
The definition provided is just saying that the set of all $omegainOmega$ for which the above mapping is continuous is required to have probability measure 1.
answered Jan 2 at 7:44
user375366user375366
885138
885138
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