Results 1 to 10 of about 165,261 (262)
Bayesian estimates of linkage disequilibrium [PDF]
BMC Genetics, 2007 The maximum likelihood estimator of D'--a standard measure of linkage disequilibrium--is biased toward disequilibrium, and the bias is particularly evident in small samples and rare haplotypes.This paper proposes a Bayesian estimation of D' to address this problem.
Sebastiani, Paola, Abad-Grau, María M.
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Default priors for density estimation with mixture models [PDF]
, 2010 The infinite mixture of normals model has become a popular method for density estimation problems. This paper proposes an alternative hierarchical model that leads to hyperparameters that can be interpreted as the location, scale and smoothness of the ...
Griffin, Jim E.
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A Bayesian “Sandwich” for Variance Estimation
Statistical Science11 pages, 2 ...
Li, Kendrick, Rice, Kenneth
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Nonparametric Bayesian Volatility Estimation [PDF]
SSRN Electronic Journal, 2018 Given discrete time observations over a fixed time interval, we study a nonparametric Bayesian approach to estimation of the volatility coefficient of a stochastic differential equation. We postulate a histogram-type prior on the volatility with piecewise constant realisations on bins forming a partition of the time interval. The values on the bins are
Gugushvili, S. +3 more
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Bayesian curve estimation by model averaging [PDF]
, 2003 A bayesian approach is used to estimate a nonparametric regression model. The main features of the procedure are, first, the functional form of the curve is approximated by a mixture of local polynomials by Bayesian Model Averaging (BMA); second, the ...
Peña, Daniel, Redondas, María Dolores
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Bayesian estimation of a Markov-switching threshold GARCH model with Student-t innovations
, 2009 A Bayesian estimation of a regime-switching threshold asymmetric GARCH model is proposed. The specification is based on a Markov-switching model with Student-t innovations and K separate GJR(1,1) processes whose asymmetries are located at ...
Ardia, David
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Benchmarking Bayesian quantum estimation
The quest for precision in parameter estimation is a fundamental task in different scientific areas. The relevance of this problem thus provided the motivation to develop methods for the application of quantum resources to estimation protocols.
Cimini, Valeria +4 more
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Classification of chirp signals using hierarchical bayesian learning and MCMC methods [PDF]
, 2002 This paper addresses the problem of classifying chirp signals using hierarchical Bayesian learning together with Markov chain Monte Carlo (MCMC) methods.
Davy, Manuel +5 more
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Bayesian Markov Blanket Estimation
CoRR, 2015 16 pages, 5 ...
Kaufmann Dinu +5 more
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Bayesian Estimation of Unknown Heteroscedastic Variances [PDF]
We propose a Bayesian procedure to estimate possibly heteroscedastic variances of the regression error term, without assuming any structure on them. What we propose in this paper, may be construed as a Conditional Bayesian procedure that is conditioned ...
Tsunemasa Shiba, Hiroaki Chigira
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