Lecture #5: Stationary Probability for a Markov Chain with Examples

For Book: See the link amzn.to/2NirzXT
This video will discuss the Stationary/Steady-state probability distribution for the Markov Chain.
#OptimizationProbStat
Other videos‪@DrHarishGarg‬
Lecture 1: Markov Chain & TPM: • Lecture #1: Stochastic...
Lecture 2: Problems using TPM Part 1: • Lecture #2: Solved Pro...
Lecture 3: Problems using TPM Part 2: • Lecture #3: Solved Pro...
Lecture 4: Problems using TPM Part 3: • Lecture #4: Solved Exa...
Lecture 5: Stationary Probabilities: • Lecture #5: Stationary...
Lecture 6: Chapman-Kolmogorov Equation & Theorem: • Chapman-Kolmogorov Equ...

[@lydiajoshua5125]

Hello Dr.Harish,
Thank you so much for your absolutely mind blowing explanations of the Markov chain model. You have a very special gift of breaking down complicated topics. I went through a number of videos before I got to yours and I am so glad I found your channel.

[@DrHarishGarg]

My pleasure.... Thanks for watching...
You can watch full course related to Probability, Statistics and Testing of Hypothesis through my video. Definitely you will learn full. See the playlist in my channel

[@lydiajoshua5125]

Thank you so much for your reply. I will watch all your videos on statistics on your channel.

[@breaktask7132]

Your teaching technique is very systematic it helps to create a study flow 🙇‍♂

[@pradeepbhambhoo8941]

Hey harish, great work man. Kudos to your hardwork and deep understanding of MC. Spent good learning time here, Thanks.

[@DrHarishGarg]

Many thanks for your appreciation. Keep watching other parts of MC also. I hope you can enjoy alot. Keep sharing with others.

[@pradeepbhambhoo8941]

@@DrHarishGarg Sure Man. Open the option for donation.

[@AnilSharma-qf5lh]

Great work sir. I am also from IIT roorkee. Nice to see a Thomsonian!

[@DrHarishGarg]

Nice... Glad to see... Kindly share the video to all the students. Hope someone get benefit from the series of the lecture.

[@tezikubaazizi]

Thank you so much Doctor. Really you have content

[@ciudadesoscuras]

Thank you Dr. Harish.

[@veerabhadrayyakalacharanti4051]

thank you sir

[@sunandapatra2774]

Thank you sir ,your teaching process is too much helpful for me

[@DrHarishGarg]

My pleasure. Keep watching and sharing.

[@saikeerthana4809]

Thank you soooo much... Your channel helped me alot!!!! ❤️

[@DrHarishGarg]

Its my pleasure..... Kindly share with others too

[@anshultyagi3696]

One more thing , if it is possible ,please upload lectures for econometrics,
Your way of teaching is really awesome..
Thank you so much sir...

[@DrHarishGarg]

Let me know the content/ topic needed

[@anshultyagi3696]

@@DrHarishGarg Estimation theory: UMVUE, AND COMPLETENESS.
ECONOMETRICS: Sir i am preparing for UPSC ISS EXAM, and i never studied econometrics during my PG,it was not in my core subjects,it is completely new for me, SO I want to make you a request please upload a series of econometrics lectures for the Indian Statistical Service exam or any other..
I will be greatful to you sir.....
Please.....

[@akanksha0143]

It's very interesting...

[@anirudhsanjeev3998]

Loved your series sir!

[@DrHarishGarg]

Glad to hear it!
Always welcome... Thanks for comment and watching... Hope you can share with others too

[@fuzzyscoop800]

Respected Sir, Thank you for valuable videos .
Can you please upload Classification of States and Chapman Equation ?

[@DrHarishGarg]

OK. I will

[@mrsmile1387]

if possible can you share the link for classification of states ?

[@fuzzyscoop800]

@@mrsmile1387, I didn't get the link for the classification of states. If you cannot find the video, please look at other resources.
Thank you.

[@ai.art_ara]

Sir, please post lecture on classification of markov chain. Thank you, great videos!

[@DrHarishGarg]

Will try

[@ai.art_ara]

@@DrHarishGarg Will wait, sir ✨

[@ekammaths3860]

Thnku so much sir..🙏🙏🙏

[@DD-bl8ql]

thanks

[@m-coder2266]

In example 5 how did you find the initial probabilities?

[@monalishagogoi1478]

Thanks for your valuable video.....sir when you upload the next video "classificationof the states of the Markov Chain"??

[@aps2412]

Awesome content Sir. Can you please point me to the next lecture on classification of states. I could not find it in your channel. Thanks

[@DrHarishGarg]

Very soon, will upload

[@abhijeetkumarmaurya4697]

Sir how to find stationary distribution for reducible MC

[@vrushali6276]

Sir pls upload irreducibility and other topics of Markov chain

[@DrHarishGarg]

Will try to upload

[@itz_shivii]

sir ne ye equations kese solve ki hai plzzz tellllll

[@anshultyagi3696]

Sir when will come lecture number 6

[@priteshgohil7026]

In your example 3 i am getting all the q as [0,0,0] i think you should show that how you calculated this p1,p2,p3 values

[@DrHarishGarg]

Remember that You should consider any two equations and one equation must be q1+q2+q3=1 during solving.

[@priteshgohil7026]

@@DrHarishGarg now I got it thank you sir.

[@amritaajain2170]

Sir did you upload classification of the states of markov chain ? Continuation of this topic ???

[@DrHarishGarg]

Still not uploaded.... But i will upload soon.

[@amritaajain2170]

Ok sir thank you

[@Mohangauri]

Can you please suggest a book to practice stochastic process questions for competitive exams?

[@DrHarishGarg]

For Book: See the link amzn.to/2NirzXT

[@shrawankumarpatel2148]

🎯🎓🎓🎓🇮🇳

[@laxmividyaclasses9770]

Let {Xn} be a stationary Markov chain such that
P(Xi+1=1|Xi=1)=p1=1-P(Xi+1=0|Xi=1)
P(Xi+1=1|Xi=0)=p0=1-P(Xi+1=0|Xi=0)
and
P(X1=1)=π1=1-P(X1=0) then
π1=p0/(1-p1+p0)
How???

[@DrHarishGarg]

This is easy... Construct a 2x2 TPM matrix of Xi and X_i+1 with state 0 and 1. So your TPM is
[1-p0 p0
1-p1 p1].
Now compute the stationary probability, we will get the required result.
Best wishes. Hope it clears.

[@problem4643]

How you solve the eq >?

[@DrHarishGarg]

Simple use the calculator ElSE using A^(-1)B

[@problem4643]

@@DrHarishGarg Can you please send me some resources coz I am having quiz in next 2 hour. Thankss

[@kusumkumari6894]

Thank you sir

[@DrHarishGarg]

My pleasure

[@ritanshitrivedi4278]

Thank you sir