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 $X(t)[omega]$?



enter image description here










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$endgroup$

















    0












    $begingroup$


    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 $X(t)[omega]$?



    enter image description here










    share|cite|improve this question









    $endgroup$















      0












      0








      0


      0



      $begingroup$


      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 $X(t)[omega]$?



      enter image description here










      share|cite|improve this question









      $endgroup$




      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 $X(t)[omega]$?



      enter image description here







      stochastic-processes






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      asked Jan 1 at 23:57









      DLBDLB

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      548






















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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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            $begingroup$

            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.






            share|cite|improve this answer









            $endgroup$


















              3












              $begingroup$

              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.






              share|cite|improve this answer









              $endgroup$
















                3












                3








                3





                $begingroup$

                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.






                share|cite|improve this answer









                $endgroup$



                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.







                share|cite|improve this answer












                share|cite|improve this answer



                share|cite|improve this answer










                answered Jan 2 at 7:44









                user375366user375366

                885138




                885138






























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