Search results for "Bayesian Inference"

Use of hierarchical Bayesian framework in MTS studies to model different causes and novel possible forms of acquired MTS

2015

Abstract: An integrative account of MTS could be cast in terms of hierarchical Bayesian inference. It may help to highlight a central role of sensory (tactile) precision could play in MTS. We suggest that anosognosic patients, with anesthetic hemisoma, can also be interpreted as a form of acquired MTS, providing additional data for the model.

Learning Bayesian Metanetworks from Data with Multilevel Uncertainty

2006

Managing knowledge by maintaining it according to dynamic context is among the basic abilities of a knowledge-based system. The two main challenges in managing context in Bayesian networks are the introduction of contextual (in)dependence and Bayesian multinets. We are presenting one possible implementation of a context sensitive Bayesian multinet-the Bayesian Metanetwork, which implies that interoperability between component Bayesian networks (valid in different contexts) can be also modelled by another Bayesian network. The general concepts and two kinds of such Metanetwork models are considered. The main focus of this paper is learning procedure for Bayesian Metanetworks.

A Bayesian Learning Automata-Based Distributed Channel Selection Scheme for Cognitive Radio Networks

2014

We consider a scenario where multiple Secondary Users SUs operate within a Cognitive Radio Network CRN which involves a set of channels, where each channel is associated with a Primary User PU. We investigate two channel access strategies for SU transmissions. In the first strategy, the SUs will send a packet directly without operating Carrier Sensing Medium Access/Collision Avoidance CSMA/CA whenever a PU is absent in the selected channel. In the second strategy, the SUs implement CSMA/CA to further reduce the probability of collisions among co-channel SUs. For each strategy, the channel selection problem is formulated and demonstrated to be a so-called "Potential" game, and a Bayesian Lea…

Multiscale variation in drought controlled historical forest fire activity in the boreal forests of eastern Fennoscandia

2017

Forest fires are a key disturbance in boreal forests, and characteristics of fire regimes are among the most important factors explaining the variation in forest structure and species composition. The occurrence of fire is connected with climate, but earlier, mostly local-scale studies in the northern European boreal forests have provided little insight into fire-climate relationship before the modern fire suppression period. Here, we compiled annually resolved fire history, temperature, and precipitation reconstructions from eastern Fennoscandia from the mid-16th century to the end of the 19th century, a period of strong human influence on fires. We used synchrony of fires over the network…

Application of a Bayesian Spatiotemporal Surveillance Method to NYC Syndromic Data

2014

Incorporating prior knowledge (e.g., the spatial distribution of zip codes and background population effects) into a model using Bayesian methods could potentially improve outbreak detection. We adapted a previously described Bayesian model-based spatiotemporal surveillance technique to daily respiratory syndrome counts in NYC Emergency Department data in 2009, the year of the H1N1 influenza pandemic. Citywide, 56 alarms were produced across 15 zip codes, all during days of elevated respiratory visits. Future work includes evaluating our choice of baseline length, considering other alarm thresholds, and conducting a formal evaluation of the method across five syndromes in NYC.

Recent statistical advances and applications of species distribution modeling

2019

En el mundo en que vivimos, producimos aproximadamente 2.5 quintillones de bytes de datos por día. Esta enorme cantidad de datos proviene de las redes sociales, Internet, satélites, etc. Todos estos datos, que se pueden registrar en el tiempo o en el espacio, son información que puede ayudarnos a comprender la propagación de una enfermedad, el movimiento de especies o el cambio climático. El uso de modelos estadísticos complejos ha aumentado recientemente en el contexto del estudio de la distribución de especies. Esta complejidad ha hecho que los procesos inferenciales y predictivos sean difíciles de realizar. El enfoque bayesiano se ha convertido en una buena opción para lidiar con estos m…

Estimating the Bayesian posterior distribution of indirect effects in causal longitudinal mediation analysis

Many research studies aim to unveil the causal mechanism underlying a particular phenomenon; mediation analysis is increasingly used for this scope, and longitudinal data are particularly suited for mediation since they ensure the correct temporal order among variables and the time spanning allows the causal effects to unfold. This explains the rise of interest in the topic of longitudinal mediation analysis. Many approaches have been proposed to cope with longitudinal mediation (Fosen et al., 2005; Lin et al., 2017), among which mixed-effect modelling. In a recent paper, Bind et al. (Biostatistics, 2016) made use of generalised mixed effect models and provided conditions for the identifiab…

Prostate Cancer Segmentation from Multiparametric MRI Based on Fuzzy Bayesian Model

2014

International audience

The Bayesian estimation of private investment in Finland

2009

Abstract This paper estimates an investment equation for private investment using Bayesian estimation techniques. In the paper we derive the optimal capital accumulation behavior in the model economy from the households’ optimization problem of utility. The equation is derived as in Smets and Wouters (2003). The model contains costly adjustment of investment and random shocks to adjustment cost function. The driving variable of investment is Tobin Q variable. The empirical proxy for Tobin Q in this paper is the ratio of OMX Helsinki Cap Index to the price index of the physical capital. The investment series is the seasonally adjusted private investment in quarterly national accounts. The AR…

The Spatial Overlap of Police Calls Reporting Street-Level and Behind-Closed-Doors Crime: A Bayesian Modeling Approach

2021

Traditionally, intimate-partner violence has been considered a special type of crime that occurs behind closed doors, with different characteristics from street-level crime. The aim of this study is to analyze the spatial overlap of police calls reporting street-level and behind-closed-doors crime. We analyzed geocoded police calls in the 552 census-block groups of the city of Valencia, Spain, related to street-level crime (N = 26,624) and to intimate-partner violence against women (N = 11,673). A Bayesian joint model was run to analyze the spatial overlap. In addition, two Bayesian hierarchical models controlled for different neighborhood characteristics to analyze the relative risks. Resu…