Timeline for Markov models with conditional transition probabilities
Current License: CC BY-SA 3.0
7 events
| when toggle format | what | by | license | comment | |
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| Jul 30, 2014 at 14:42 | comment | added | Aaron Johnson | I didn't immediately pick your answer because I was waiting for more candidates. They never came, and I forgot about it. Two years later, I now award you by accepting your answer. Thanks for the info! By the way, have you come across anything else on this topic in the last two years? It's still something that I'm interested in. | |
| Jul 30, 2014 at 14:40 | vote | accept | Aaron Johnson | ||
| Mar 19, 2012 at 20:12 | comment | added | jkt | I am not an expert, but I guess the results should hold for continuous case in general. Kalman filter for instance runs on an HMM (1st order markov chain) with continuous states. | |
| Mar 19, 2012 at 16:02 | comment | added | Aaron Johnson | +1 to your answer for the reference to the Ching, Ng, and Fung paper. That's a good one to have. However, after reading through it, it appears that it only covers discrete variables (which is kind of what I expected.) While I can discretize my continuous variables, I'm still curious -- Are there any models that can handle the raw continuous variables? | |
| Mar 12, 2012 at 6:27 | comment | added | jkt | There is a paper you can check. It first starts describing 1st order chains, then describes the situation for higher order chains. (Higher-order multivariate Markov chains and their applications by Ching,Ng,Fung) If you are interested in machine learning kind of stuff, I suggest you to check Kevin Murphy's website. He also has a MATLAB toolbox that you can play with. | |
| Mar 12, 2012 at 6:04 | comment | added | Aaron Johnson | YBE, Thanks for the quick reply! Does this (modeling the system as a 2nd order or higher chain) allow me to model continuous covariates, or just discrete covariates? And can you point me to a link that gives a good example of what you're talking about? Thanks! | |
| Mar 9, 2012 at 18:29 | history | answered | jkt | CC BY-SA 3.0 |