Convergence rate of Markov chain methods for genomic motif discovery
نویسندگان
چکیده
منابع مشابه
Convergence Rate of Markov Chain Methods for Genomic Motif Discovery
We analyze the convergence rate of a popular Gibbs sampling method used for statistical discovery of gene regulatory binding motifs in DNA sequences. This sampler satisfies a very strong form of ergodicity (uniform). However, we show that, due to multimodality of the posterior distribution, the rate of convergence often decreases exponentially as a function of the length of the DNA sequence. Sp...
متن کاملWeb Appendix for “ Convergence Rate of Markov Chain Methods for Genomic Motif
• w: fixed motif length. • L: length of the observed nucleotide sequence S. • M : known number of nucleotide types (typically =4 in practice). • J : number of motifs in the generative model (defined in Assumption 3.2) • p0: fixed motif frequency in the inference model (defined Section 2.1). • S = (S1, . . . , SL): observed sequence of nucleotides (defined Sec. 2.1). • A = (A1, . . . , AL/w): un...
متن کاملConvergence Rate of Markov Chain Methods for Genomic Motif Discovery1 by Dawn
We analyze the convergence rate of a simplified version of a popular Gibbs sampling method used for statistical discovery of gene regulatory binding motifs in DNA sequences. This sampler satisfies a very strong form of ergodicity (uniform). However, we show that, due to multimodality of the posterior distribution, the rate of convergence often decreases exponentially as a function of the length...
متن کاملanalysis of ruin probability for insurance companies using markov chain
در این پایان نامه نشان داده ایم که چگونه می توان مدل ریسک بیمه ای اسپیرر اندرسون را به کمک زنجیره های مارکوف تعریف کرد. سپس به کمک روش های آنالیز ماتریسی احتمال برشکستگی ، میزان مازاد در هنگام برشکستگی و میزان کسری بودجه در زمان وقوع برشکستگی را محاسبه کرده ایم. هدف ما در این پایان نامه بسیار محاسباتی و کاربردی تر از روش های است که در گذشته برای محاسبه این احتمال ارائه شده است. در ابتدا ما نشا...
15 صفحه اولMarkov Chain Decomposition for Convergence Rate Analysis
In this paper we develop tools for analyzing the rate at which a reversible Markov chain converges to stationarity. Our techniques are useful when the Markov chain can be decomposed into pieces which are themselves easier to analyze. The main theorems relate the spectral gap of the original Markov chains to the spectral gap of the pieces. In the first case the pieces are restrictions of the Mar...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: The Annals of Statistics
سال: 2013
ISSN: 0090-5364
DOI: 10.1214/12-aos1075