A Random Time for Simulating Markov Chains
碩士 === 國立交通大學 === 應用數學系數學建模與科學計算碩士班 === 103 === In this thesis, we provided a simulated method, which can avoid lots of computations, to make the Markov chain approximate its stationary distribution and also gave a theorem to prove it. At first part, we gave a theorem to prove the convergence of new...
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| Format: | Others |
| Language: | en_US |
| Published: |
2015
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| Online Access: | http://ndltd.ncl.edu.tw/handle/46061230095924119836 |
| Summary: | 碩士 === 國立交通大學 === 應用數學系數學建模與科學計算碩士班 === 103 === In this thesis, we provided a simulated method, which can avoid lots of computations, to make the Markov chain approximate its stationary distribution and also gave a theorem to prove it. At first part, we gave a theorem to prove the convergence of new random variable. At second part, we gave two special cases of simulation and found the random variable will not converge to the stationary distribution if the chain does not satisfy the condition of theorem. At last, we gave a way to improve the chain.
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