Markov Matrices

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MIT 18.06SC Linear Algebra, Fall 2011
Instructor: David Shirokoff

A teaching assistant works through a problem on Markov matrices.

License: Creative Commons BY-NC-SA

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Huge thanks to you!! Very clearly explained at a comfort pace. Its nearly final and my teacher's only covering the theorems and some calculation examples. This mit series really showed me what matrices could achieve and the connection between concepts. (I especially like the fibonacci part and this partical part) Good job!

boruiwang

Herein we observe an advantage of being left-handed. :)

DirkGently-pv

Such brief and impeccable lecture

Totally enjoying it

prajyot

Thank you! Good explanation.
But I think it is not necessary to calculate the decomposition A = UDU-1.

We know that the probability after k steps is Pk = c(λ1)(^k)x1 + d(λ2)(^k)x2 where x1 and x2 are the eigenvectors and λ1, λ2 the eigenvalues, with P0 we can calculate the coefficients c and d for k=0. After 100 steps the probability is Pk for k = 100.

fedepan

Best one yet. Really cleared everything up in this chapter.

surajmirchandani

So interesting lecture and problem on Markov matrix!

박현진-dhd

The Markov matrix A is a transpose of what is usually presented.

stephenclark

So I sort of understand right until the end. With the final probability for n = infinity, being one third, one in two; how does that translate to the answer to the question 'What is the probability it is at A and B after an infinite number of steps'. Is the answer that it's six more times as likely to be at B than A ?

peterhind

This guy can explain things well. He says, "Welcome back." Now I’m trying to find the first video for which this video is a sequel. Could someone tell me where that first video is?

kostikoistinen

Very good video and very clearly explained.

AnupKumar-wked

I get different eigenvalues: (1, -0.2)

ricardoV

This guy reminds me of Will from good Will hunting

richard_guang

For an MIT solution, it lacks some proof. We do not always see, we need a detailed explanation.
But it is fine.

reginalnzubehimuonaka

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