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Bayasgulang, Uyugunsandan
(World Oral Literature Project, 201211)Bayasgualng, an amateur bard who has a passion for singing by playing the instrument called dörben utasutu hugur (four stringed fiddle). Uyugunsandan is a Horchin love song named after the female character of the song. In ... 
Bayasgulang, Yandan Güngjü
(World Oral Literature Project, 201211)Bayasgualng, an amateur bard who has a passion for singing by playing the instrument called dörben utasutu hugur (four stringed fiddle). Although the song Yandan Güngjü was a figure from Chinese classical story, the song ... 
Bayesian Estimation of RiskPremia in an APT Context
(20040616)Recognizing the problems of estimation error in computing risk premia via arbitrage pricing, this paper provides a Bayesian methodology for estimating factor risk premia and hence equity risk premia for both traded and ... 
A Bayesian adaptive design for biomarker trials with linked treatments
(NPG, 20150811)background: Response to treatments is highly heterogeneous in cancer. Increased availability of biomarkers and targeted treatments has led to the need for trial designs that efficiently test new treatments in biomarkerstratified ... 
Bayesian analysis for inference of an emerging epidemic: citrus canker in urban landscapes.
(Public Library of Science (PLoS), 20140424)Outbreaks of infectious diseases require a rapid response from policy makers. The choice of an adequate level of response relies upon available knowledge of the spatial and temporal parameters governing pathogen spread, ... 
Bayesian Analysis of the BlackScholes Option Price
(20040616)This paper investigates the statistical properties of the BlackScholes option price under a Bayesian approach. We incorporate randomness, both in the price process and in volatility, to derive the prior and posterior ... 
Bayesian changepoint analysis reveals developmental change in a classic theory of mind task
(Elsevier, 201610)Although learning and development reflect changes situated in an individual brain, most discussions of behavioral change are based on the evidence of group averages. Our reliance on groupaveraged data creates a dilemma. ... 
A Bayesian Confidence Interval for ValueatRisk
(20040616)This study assesses the accuracy of the valueatrisk estimate (VaR). On the basis of posterior distributions of the unknown population parameters, we develop a confidence interval for VaR that reflects the genuine ... 
Bayesian Forecasting of Options Prices: A Natural Framework for Pooling Historical and Implied Volatiltiy Information
(20040616)Bayesian statistical methods are naturally oriented towards pooling in a rigorous way information from separate sources. It has been suggested that both historical and implied volatilities convey information about future ... 
Bayesian generalised ensemble Markov chain Monte Carlo
(Microtome Publishing, 2016)Bayesian generalised ensemble (BayesGE) is a new method that addresses two major drawbacks of standard Markov chain Monte Carlo algorithms for inference in highdimensional probability models: inapplicability to estimate ... 
Bayesian Inference of Accurate Population Sizes and FRET Efficiencies from Single Diffusing Biomolecules
(ACS, 20140808)It is of significant biophysical interest to obtain accurate intramolecular distance information and population sizes from singlemolecule Förster resonance energy transfer (smFRET) data obtained from biomolecules in ... 
Bayesian Inference of TaskBased Functional Brain Connectivity Using Markov Chain Monte Carlo Methods
(IEEE, 20161001)The study of functional networks in the brain is essential in order to gain a better insight into its diverse set of operations and to characterise the associated normal and abnormal behaviours. Present methods of analysing ... 
Bayesian Learning For The Type3 Joint Sparse Signal Recovery
(IEEE, 2016)Compressed sensing (CS) is a signal acquisition paradigm that utilises the finding that a small number of linear projections of a sparse signal have enough information for stable recovery. This paper develops a Bayesian ... 
A Bayesian method for microseismic source inversion
(Oxford University Press, 20160518)Earthquake source inversion is highly dependent on location determination and velocity models. Uncertainties in both the model parameters and the observations need to be rigorously incorporated into an inversion approach. ... 
Bayesian methods for gravitational waves and neural networks
(20121009)Einstein’s general theory of relativity has withstood 100 years of testing and will soon be facing one of its toughest challenges. In a few years we expect to be entering the era of the first direct observations of ... 
Bayesian methods for metaanalysis of causal relationships estimated using genetic instrumental variables
(Wiley, 20100308)Genetic markers can be used as instrumental variables, in an analogous way to randomization in a clinical trial, to estimate the causal relationship between a phenotype and an outcome variable. Our purpose is to extend the ... 
Bayesian methods in music modelling
(20110315)This thesis presents several hierarchical generative Bayesian models of musical signals designed to improve the accuracy of existing multiple pitch detection systems and other musical signal processing applications whilst ... 
Bayesian Model Choice in Cumulative Link Ordinal Regression Models
(International Society for Bayesian Analysis, 20150128)The use of the proportional odds (PO) model for ordinal regression is ubiquitous in the literature. If the assumption of parallel lines does not hold for the data, then an alternative is to specify a nonproportional odds ... 
Bayesian regularization of the length of memory in reversible sequences
(Wiley, 20151016)Variable order Markov chains have been used to model discrete sequential data in a variety of fields. A host of methods exist to estimate the historydependent lengths of memory which characterize these models and to predict ... 
Bayesian source inversion of microseismic events
(20160105)Rapid stress release at the source of an earthquake produces seismic waves. Observations of the particle motions from such waves are used in source inversion to characterise the dynamic behaviour of the source and to help ...