chapter 3 markov chains

Discussion in 'CT4' started by SURESH SHARMA, Jun 21, 2016.

  1. SURESH SHARMA

    SURESH SHARMA Member

    can any explain the proof in study material section 5.3 Random Walk on s={...-2,-1,0,1,2....}

    The Markov property Holds:
    P[Xn=J|X1=i1,......Xm-1=im-1,Xm=i]
    P[Xm+Ym+1+...Yn=j|X1=i1,....Xm-1=im-1,Xm=i]
    P[Ym+1+....Yn=j-i]= P[Xn=j|Xm=i]

    please explain the second and third line.

    regards

    Suresh sharma
    9051838188
     
  2. Julie Lewis

    Julie Lewis Member

    What page is this from? Please give a full course reference.
     
  3. SURESH SHARMA

    SURESH SHARMA Member


    Hi

    its in page 20 of chapter 3 markov chain section 5.3 of study material.
     
  4. Julie Lewis

    Julie Lewis Member

    It's not on page 20 of the 2016 course notes.
     
  5. SURESH SHARMA

    SURESH SHARMA Member


    ok please explain i am writing down the whole thing:



    Simple Random Walk on S ={....-2,-1,0,1,2.....}

    This is defined as Xn = Y1+Y2+.......+Yn where the random variable Yj (the steps of the walk ) are mutually independent with common probability distribution:

    P[Yj=1]=p, P[Yj=-1] =1-p

    The Markov Property Holds :

    P[Xn=J|X1=i1,......Xm-1=im-1,Xm=i]
    P[Xm+Ym+1+...Yn=j|X1=i1,....Xm-1=im-1,Xm=i]
    P[Ym+1+....Yn=j-i]= P[Xn=j|Xm=i]

    please explain the second and third line.
     
  6. John Potter

    John Potter ActEd Tutor Staff Member

    Hi Suresh,

    The second line is replacing Xn with Xm plus the steps Y between times m and n. X is a process that adds up the Ys
    The third line has subtracred Xm from the LHS and j from the RHS. This is OK because Xm=j

    One thing that is massively helpful for everyone is if you can give full course references when you post queries. It's great when students can help each other and also really useful for the tutors if we feel that our input is needed.

    I notice that you've also posted your algorithm for others to look at. This is great, well done!

    Good luck!
    John
     

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