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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The trajectory of customer loyalty: an empirical test of Dick and Basu’s loyalty framework
TL;DR: This article examined the key drivers of shifts in consumers' loyalty conditions over six annual time periods and found that marketing actions, such as private label policy, feature advertising, end-of-aisle product display, and store pricing policy, influence customer transition across loyalty conditions.
Journal ArticleDOI
Improved state change estimation in dynamic functional connectivity using hidden semi-Markov models.
TL;DR: A hidden semi‐Markov model (HSMM) approach for inferring time‐varying brain networks from fMRI data, which explicitly models the sojourn distribution, and demonstrates the importance of model choice when estimatingSojourn times and reveals their potential for understanding healthy and diseased brain mechanisms.
Proceedings ArticleDOI
Supervised intentional process models discovery using Hidden Markov models
TL;DR: The aim of this paper is to propose the use of probabilistic models to evaluate the most likely intentions behind traces of activities, namely Hidden Markov Models (HMMs).
Journal Article
Application of Hidden Markov Models and Hidden Semi-Markov Models to Financial Time Series
TL;DR: A hybrid algorithm that is designed to combine the advantageous features of the EM and DNM algorithms is proposed, and the performance of the three algorithms (EM, DNM and the hybrid) are compared.
Journal ArticleDOI
Improving detection of copy-number variation by simultaneous bias correction and read-depth segmentation
TL;DR: A novel read-depth–based method, GENSENG, is presented, which uses a hidden Markov model and negative binomial regression framework to identify regions of discrete copy-number changes while simultaneously accounting for the effects of multiple confounders.
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.