A Maximization Technique Occurring in the Statistical Analysis of Probabilistic Functions of Markov Chains
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This article is published in Annals of Mathematical Statistics.The article was published on 1970-02-01 and is currently open access. It has received 4618 citations till now. The article focuses on the topics: Examples of Markov chains & Markov chain.read more
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Journal ArticleDOI
A Hidden Markov Model Derived Structural Alphabet for Proteins
TL;DR: A hidden Markov model is set up that discretizes protein backbone conformation as series of overlapping fragments of four residues length that obtains an optimal systematic decomposition of the conformational variability of the protein peptidic chain in 27 states with strong connection logic.
Journal ArticleDOI
Detecting Neural-State Transitions Using Hidden Markov Models for Motor Cortical Prostheses
Caleb Kemere,Gopal Santhanam,Byron M. Yu,Afsheen Afshar,Stephen I. Ryu,Teresa H. Meng,Krishna V. Shenoy +6 more
TL;DR: A technique to automatically differentiate between baseline, plan, and perimovement epochs of neural activity is developed based on a hidden Markov model (HMM), which can detect transitions in neural activity corresponding to targets not found in training data.
Journal ArticleDOI
Prediction of 24-hour-average PM2.5 concentrations using a hidden Markov model with different emission distributions in Northern California
TL;DR: HMMs with log-normal, Gamma and generalized extreme value (GEV) distributions are developed to predict PM(2.5) concentration at Concord and Sacramento monitors in Northern California and show that the closer the distribution employed in HMM is to the observation sequence, the better the model prediction performance.
Proceedings ArticleDOI
Using Hidden Semi-Markov Models for Effective Online Failure Prediction
Felix Salfner,Miroslaw Malek +1 more
TL;DR: This work focuses on methods that use event-driven sources such as errors for online failure prediction and uses hidden semi-Markov models (HSMMs) for this purpose and demonstrates effectiveness based on field data of a commercial telecommunication system.
Journal ArticleDOI
BayesPeak: Bayesian analysis of ChIP-seq data
TL;DR: The proposed statistical algorithm, BayesPeak, uses a fully Bayesian hidden Markov model to detect enriched locations in the genome and is shown to provide high-confidence calls with low false positive rates.
References
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Journal ArticleDOI
Statistical Inference for Probabilistic Functions of Finite State Markov Chains
Leonard E. Baum,Ted Petrie +1 more
Journal ArticleDOI
An inequality with applications to statistical estimation for probabilistic functions of Markov processes and to a model for ecology
Leonard E. Baum,J. A. Eagon +1 more
TL;DR: In this paper, a polynomial with nonnegative coefficients homogeneous of degree d in its variables is shown to be polynomially homogeneous unless 3(3(x))>P(x), where 3(x)=x.
Book ChapterDOI
The Gamma Function
Willi Freeden,Martin Gutting +1 more
TL;DR: The Gamma function as discussed by the authors is a generalized factorial function that can be used to estimate the probability distribution of a probability distribution, and it has been used in many applications, e.g., as part of probability distributions.