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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A survey on off-line Cursive Word recognition
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A spectral algorithm for learning Hidden Markov Models
TL;DR: In this paper, the authors prove that under a natural separation condition (bounds on the smallest singular value of the HMM parameters), there is an efficient and provably correct algorithm for learning hidden Markov models.
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Shakra: tracking and sharing daily activity levels with unaugmented mobile phones
Ian Anderson,Julie Maitland,Scott Sherwood,Louise Barkhuus,Matthew Chalmers,Malcolm Hall,Barry Brown,Henk Muller +7 more
TL;DR: A prototype application that tracks the daily exercise activities of people, using an Artificial Neural Network to analyse GSM cell signal strength and visibility to estimate a user’s movement is described.
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Robust maximum-likelihood estimation of multivariable dynamic systems
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TL;DR: The theoretical and empirical evidence presented here establishes additional attractive properties such as numerical robustness, avoidance of difficult parametrization choices, the ability to naturally and easily estimate non-zero initial conditions, and moderate computational cost.
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.