Bayesian statistics & modelling

A Bayesian case-controls exploration of the malleability of attentional bias for threat in social phobia

by Alexandre Heeren

Heeren, A., Maurage, P., & Philippot, P. (in press). A Bayesian case-controls exploration of the malleability of attentional bias for threat in social phobia. International Journal of Cognitive Therapy.

A Bayesian binaural system for 3D sound-source localisation

by João Filipe Ferreira

Dynamic Patterns of Time Use in Adolescence

by Brian Flaherty

Using Data Augmentation to Obtain Standard Errors and Conduct Hypothesis Tests in Latent Class and Latent Transition Analysis

by Brian Flaherty

Bayesian mixture modeling of gene-environment and gene-gene interactions.

by Frank de Vocht

Genet Epidemiol. 2010 Jan;34(1):16-25.

With the advent of rapid and relatively cheap genotyping technologies there is now the opportunity to attempt to... more With the advent of rapid and relatively cheap genotyping technologies there is now the opportunity to attempt to identify gene-environment and gene-gene interactions when the number of genes and environmental factors is potentially large. Unfortunately the dimensionality of the parameter space leads to a computational explosion in the number of possible interactions that may be investigated. The full model that includes all interactions and main effects can be unstable, with wide confidence intervals arising from the large number of estimated parameters. We describe a hierarchical mixture model that allows all interactions to be investigated simultaneously, but assumes the effects come from a mixture prior with two components, one that reflects small null effects and the second for epidemiologically significant effects. Effects from the former are effectively set to zero, hence increasing the power for the detection of real signals. The prior framework is very flexible, which allows substantive information to be incorporated into the analysis. We illustrate the methods first using simulation, and then on data from a case-control study of lung cancer in Central and Eastern Europe.

Quand est-ce que le Président Sarkozy a perdu la confiance des Français

by Matthieu Authier

Foraging Strategy and Longevity in Male Southern Elephant Seals

by Matthieu Authier

Bayesian evidence for two companions orbiting HIP 5158

by Sreekumar Thaithara Balan

F. Feroz , S. T. Balan , M. P. Hobson, MNRAS, 2011, 416, 1, L104-L108

We present results of a Bayesian analysis of radial velocity data for the star HIP 5158, confirming the presence of... more We present results of a Bayesian analysis of radial velocity data for the star HIP 5158, confirming the presence of two companions and also constraining their orbital parameters. Assuming Keplerian orbits, the two-companion model is found to be e48 times more probable than the one-planet model, although the orbital parameters of the second companion are only weakly constrained. The derived orbital periods are 345.6 ± 2.0 and 9017.8 ± 3180.7 d, respectively, and the corresponding eccentricities are 0.54 ± 0.04 and 0.14 ± 0.10. The limits on planetary mass (m sin i) and semimajor axis are (1.44 ± 0.14MJ, 0.89 ± 0.01 au) and (15.04 ± 10.55MJ, 7.70 ± 1.88 au), respectively. Owing to the large uncertainty on the mass of the second companion, we are unable to determine whether it is a planet or a brown dwarf. The remaining 'noise' (stellar jitter) unaccounted for by the model is 2.28 ± 0.31 m s-1. We also analysed a three-companion model, but found it to be e8 times less probable than the two-companion model

Detecting extrasolar planets from stellar radial velocities using Bayesian evidence

by Sreekumar Thaithara Balan

F. Feroz , S. T. Balan, M. P. Hobson, MNRAS, 2011, 415,4, 3462-3472

Stellar radial velocity (RV) measurements have proven to be a very successful method for detecting extrasolar planets.... more Stellar radial velocity (RV) measurements have proven to be a very successful method for detecting extrasolar planets. Analysing RV data to determine the parameters of the extrasolar planets is a significant statistical challenge owing to the presence of multiple planets and various degeneracies between orbital parameters. Determining the number of planets favoured by the observed data is an even more difficult task. Bayesian model selection provides a mathematically rigorous solution to this problem by calculating marginal posterior probabilities of models with different number of planets, but the use of this method in extrasolar planetary searches has been hampered by the computational cost of the evaluating Bayesian evidence. None the less, Bayesian model selection has the potential to improve the interpretation of existing observational data and possibly detect yet undiscovered planets. We present a new and efficient Bayesian method for determining the number of extrasolar planets, as well as for inferring their orbital parameters, without having to calculate directly the Bayesian evidence for models containing a large number of planets. Instead, we work iteratively and at each iteration obtain a conservative lower limit on the odds ratio for the inclusion of an additional planet into the model. We apply this method to simulated data sets containing one and two planets and successfully recover the correct number of planets and reliable constraints on the orbital parameters. We also apply our method to RV measurements of HD 37124, 47 Ursae Majoris and HD 10180. For HD 37124, we confirm that the current data strongly favour a three-planet system. We find strong evidence for the presence of a fourth planet in 47 Ursae Majoris, but its orbital period is suspiciously close to 1 yr, casting doubt on its validity. For HD 10180 we find strong evidence for a six-planet system.

EXOFIT: Bayesian Estimation of Orbital Parameters of Extrasolar Planets

by Sreekumar Thaithara Balan

Sreekumar T. Balan  and Ofer Lahav, Proceedings of Molecules in the Atmospheres of Extrasolar Planets

We introduce EXOFIT, a Bayesian tool for estimating orbital parameters of extrasolar planets from radial velocity... more We introduce EXOFIT, a Bayesian tool for estimating orbital parameters of extrasolar planets from radial velocity measurements. EXOFIT can search for either one or two planets at present. EXOFIT employs Markov Chain Monte Carlo method implemented in an object oriented manner. As an example we re-analyze the orbital solution of HD155358 and the results are compared with that of the published orbital parameters. In order to check the agreement of the EXOFIT orbital parameters with the published ones we examined radial velocity data of 30 stars taken randomly from www.exoplanet.eu. We show that while orbital periods agree in both methods, EXOFIT prefers lower eccentricity solutions for planets with higher (e >=0.5) orbital eccentricities.

A hierarchical change-point model for estimating ontogenetic shifts with stable isotope data

by Matthieu Authier

Maternal strategies in the southern elephant seal a stable isotope investigation

by Matthieu Authier

Unveiling the At-Sea Ecology of Southern Elephant Seals from Indirect Evidence

by Matthieu Authier

A hierarchical Bayesian framework for multimodal active perception

by João Filipe Ferreira

Co-authored with M. Castelo-Branco, J. Dias, Adaptive Behavior, published online ahead of print, March 1st, 2012.

In this article, we present a hierarchical Bayesian framework for multimodal active perception, devised to be... more In this article, we present a hierarchical Bayesian framework for multimodal active perception, devised to be emergent, scalable and adaptive. This framework, while not strictly neuromimetic, finds its roots in the role of the dorsal perceptual pathway of the human brain. Its composing models build upon a common spatial configuration that is naturally fitting for the integration of readings from multiple sensors using a Bayesian approach devised in previous work. The framework presented in this article is shown to adequately model human-like active perception behaviours, namely by exhibiting the following desirable properties: high-level behaviour results from low-level interaction of simpler building blocks; seamless integration of additional inputs is allowed by the Bayesian Programming formalism; initial ‘genetic imprint’ of distribution parameters may be changed ‘on the fly’ through parameter manipulation, thus allowing for the implementation of goal-dependent behaviours (i.e. top-down influences).

Bayesian flexibles modelling of mixed logit models

by marcucci edoardo

Bayes methods for combining the results of cancer studies in humans and other species

by William DuMouchel

An application of Bayesian spatial statistical methods to the study of racial and poverty segregation and infant mortality rates in the US

by Corey Sparks

The infant mortality rate is a fundamental measure of population health used internationally. In the United States,... more The infant mortality rate is a fundamental measure of population health used internationally. In the United States, the infant mortality rate is higher than what would be expected for a country of its affluence. We present an analysis of US county infant mortality rates using modern Bayesian spatial statistical methodologies. Our key predictors in our statistical analysis are residential racial and poverty segregation, measured by the dissimilarity, interaction and spatial proximity indexes. We use both Exploratory Spatial Data Analysis methods and Hierarchical Bayesian spatial regression models to examine the influences of these segregation measures on the infant mortality rate for each county, net of income inequality, degree of rurality and relative socioeconomic deprivation. The spatial measures of racial segregation suggest that when blacks live in close proximity to each other, this tends to increase the infant mortality rate. The results for poverty segregation suggest the same pattern, when poor populations live in close proximity to one another this is generally detrimental to the county infant mortality rate. However, interac- tion between blacks and whites and poor and non-poor residents of an area is protective for infant mortality.

BaSTA: an R package for Bayesian estimation of age-specific survival from incomplete mark–recapture/recovery data with covariates

by Owen Jones

published in Methods In Ecology and Evolution 2012

1. Understanding age-specific survival in wild animal populations is crucial to the study of population dynamics and... more 1. Understanding age-specific survival in wild animal populations is crucial to the study of population dynamics and is therefore an essential component of several fields including evolution, management and conservation.

2. We present Bayesian survival trajectory analysis (BaSTA), a free open-source software package for estimating age-specific survival from capture–recapture/recovery data under a Bayesian framework.

3. The method copes with low recapture probabilities, unknown ages (e.g. because of left-truncation) and unknown ages at death (e.g. because of right-censoring). It estimates survival and detection parameters as well as the unknown birth and death times (i.e. latent states) while allowing users to test a range of survival models. In addition, the effect of continuous or categorical covariates can be evaluated.

4. This tool facilitates the analysis of age patterns of survival in long-term animal studies and will enable researchers to robustly infer the effect of covariates, even with large amounts of missing data.

Unusual constraints in the quantum statistical mechanics of Josephson junction systems

by Taner Edis

Journal of Statistical Physics, 71 313 (1993)

In order to apply quantum statistical mechanics to systems composed of Josephson junctions, the unconventional... more In order to apply quantum statistical mechanics to systems composed of Josephson junctions, the unconventional constraint of fixed "macroscopic wave function" magnitudes on either side of a junction must be accommodated. In order to use this information, the density matrix formalism must be extended to deal directly with probability distributions over general quantum states. As a result, in thermal equilibrium, the explicit temperature dependence becomes modified from the trivial 1/kT factors.

Tree models: a Bayesian perspective

by Blaise Egan