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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Multiple Testing for Pattern Identification, With Applications to Microarray Time-Course Experiments
Wenguang Sun,Zhi Wei +1 more
TL;DR: A compound decision-theoretic framework for set-wise multiple testing is formulated and a data-driven procedure that aims to minimize the missed set rate subject to a constraint on the false set rate is proposed.
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Distributed Detection in Sensor Networks Over Fading Channels With Multiple Antennas at the Fusion Centre
TL;DR: In this article, the authors developed new and optimal algorithms for distributed detection in sensor networks over fading channels with multiple receive antennas at the Fusion Center (FC) where the sensors observe a hidden physical phenomenon over fading channel and transmit their observations using the amplify-and-forward scheme over the fading channels to the FC.
Journal ArticleDOI
Graphical Models for Statistical Inference and Data Assimilation
Alexander T. Ihler,Sergey Kirshner,Michael Ghil,Michael Ghil,Andrew W. Robertson,Padhraic Smyth +5 more
TL;DR: Several additional examples of how graphical models can be applied to climate dynamics, speciflcally estimation using multi-resolution models of large{scale data sets such as satellite imagery, and learning hidden Markov models to capture rainfall patterns in space and time are given.
Journal ArticleDOI
Long Memory of Financial Time Series and Hidden Markov Models with Time-Varying Parameters
TL;DR: In this paper, a two-state Gaussian hidden Markov model with time-varying parameters was used to model the long memory of squared daily returns. But the model was not able to reproduce the long-term memory of daily returns that was previously believed to be the most difficult fact to reproduce with a Hidden Markov Model.
Journal ArticleDOI
Using Genomic Inbreeding Coefficient Estimates for Homozygosity Mapping of Rare Recessive Traits: Application to Taybi-Linder Syndrome
Anne-Louise Leutenegger,Anne-Louise Leutenegger,Audrey Labalme,Emmanuelle Génin,Emmanuelle Génin,Annick Toutain,Elisabeth Steichen,Françoise Clerget-Darpoux,Françoise Clerget-Darpoux,Patrick Edery +9 more
TL;DR: The use of inbred patients whose exact genealogy may not be available is of primary interest in mapping genes involved in rare recessive diseases and it is shown that this can be achieved by estimating inbreeding coefficients from the patients' genomic information and using these estimates to perform homozygosity mapping.
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.