Search results for "Bayesian [statistical analysis]"
showing 10 items of 299 documents
Spatio-Temporal Analysis of Suicide-Related Emergency Calls
2017
Considerable effort has been devoted to incorporate temporal trends in disease mapping. In this line, this work describes the importance of including the effect of the seasonality in a particular setting related with suicides. In particular, the number of suicide-related emergency calls is modeled by means of an autoregressive approach to spatio-temporal disease mapping that allows for incorporating the possible interaction between both temporal and spatial effects. Results show the importance of including seasonality effect, as there are differences between the number of suicide-related emergency calls between the four seasons of each year.
Sequential Monte Carlo methods in Bayesian joint models for longitudinal and time-to-event data
2017
El análisis estadístico de la información generada por el seguimiento médico de una enfermedad es un reto muy importante en el ámbito de la medicina personalizada. A medida que avanza el curso evolutivo de la enfermedad en un paciente, su seguimiento genera cada vez más información que debe ser procesada inmediatamente para revisar y actualizar su pronóstico y tratamiento. Nuestro objetivo en esta tesis se centra en dicho proceso de actualización a través de métodos de inferencia secuencial en modelos conjuntos de datos longitudinales y de supervivencia desde una perspectiva Bayesiana. En concreto, proponemos la utilización de métodos secuenciales de Monte Carlo adaptados a modelos conjunto…
Generalized Bayesian Pursuit: A Novel Scheme for Multi-Armed Bernoulli Bandit Problems
2011
In the last decades, a myriad of approaches to the multi-armed bandit problem have appeared in several different fields. The current top performing algorithms from the field of Learning Automata reside in the Pursuit family, while UCB-Tuned and the e-greedy class of algorithms can be seen as state-of-the-art regret minimizing algorithms. Recently, however, the Bayesian Learning Automaton (BLA) outperformed all of these, and other schemes, in a wide range of experiments. Although seemingly incompatible, in this paper we integrate the foundational learning principles motivating the design of the BLA, with the principles of the so-called Generalized Pursuit algorithm (GPST), leading to the Gen…
Five Ways in Which Computational Modeling Can Help Advance Cognitive Science
2019
Abstract There is a rich tradition of building computational models in cognitive science, but modeling, theoretical, and experimental research are not as tightly integrated as they could be. In this paper, we show that computational techniques—even simple ones that are straightforward to use—can greatly facilitate designing, implementing, and analyzing experiments, and generally help lift research to a new level. We focus on the domain of artificial grammar learning, and we give five concrete examples in this domain for (a) formalizing and clarifying theories, (b) generating stimuli, (c) visualization, (d) model selection, and (e) exploring the hypothesis space.
Spain in the euro: a general equilibrium analysis
2010
Bayesian dynamic stochastic general equilibrium (DSGE) models combine microeconomic behavioural foundations with a full-system Bayesian likelihood estimation approach using key macro-economic variables. Because of the usefulness of this class ofmodels for addressing questions regarding the impact and consequences of alternative monetary policies they are nowadays widely used for forecasting and policy analysis at central banks and other institutions. In this paper we provide a brief description of the two main aggregate euro area models at the ECB. Both models share a common core but their detailed specification differs reflecting their specific focus and use. The New Area Wide Model (NAWM)…
Cognitive resource allocation determines the organization of personal networks
2018
Significance The way we organize our social relationships is key to understanding the structure of our society. We propose a quantitative theory to tackle this issue, assuming that our capacity to maintain relationships is limited and that different types of relationships require different investments. The theory accounts for well-documented empirical evidence on personal networks, such that connections are typically arranged in layers of increasing size and decreasing emotional content. More interestingly, it predicts that when the number of available relationships is small, this structure is inverted, having more close relationships than acquaintances. We provide evidence of the existence…
Bayesian model to detect phenotype-specific genes for copy number data
2012
Abstract Background An important question in genetic studies is to determine those genetic variants, in particular CNVs, that are specific to different groups of individuals. This could help in elucidating differences in disease predisposition and response to pharmaceutical treatments. We propose a Bayesian model designed to analyze thousands of copy number variants (CNVs) where only few of them are expected to be associated with a specific phenotype. Results The model is illustrated by analyzing three major human groups belonging to HapMap data. We also show how the model can be used to determine specific CNVs related to response to treatment in patients diagnosed with ovarian cancer. The …
Mathematical models for the diffusion magnetic resonance signal abnormality in patients with prion diseases
2014
In clinical practice signal hyperintensity in the cortex and/or in the striatum on magnetic resonance (MR) diffusion-weighted images (DWIs) is a marker of sporadic Creutzfeldt–Jakob Disease (sCJD). MR diagnostic accuracy is greater than 90%, but the biophysical mechanisms underpinning the signal abnormality are unknown. The aim of this prospective study is to combine an advanced DWI protocol with new mathematical models of the microstructural changes occurring in prion disease patients to investigate the cause of MR signal alterations. This underpins the later development of more sensitive and specific image-based biomarkers. DWI data with a wide a range of echo times and diffusion weightin…
Bayesian modeling of the evolution of male height in 18th century Finland from incomplete data.
2012
Abstract Data on army recruits’ height are frequently available and can be used to analyze the economics and welfare of the population in different periods of history. However, such data are not a random sample from the whole population at the time of interest, but instead is skewed since the short men were less likely to be recruited. In statistical terms this means that the data are left-truncated. Although truncation is well-understood in statistics a further complication is that the truncation threshold is not known, may vary from time to time, and auxiliary information on the threshold is not at our disposal. The advantage of the fully Bayesian approach presented here is that both the …
Cancer mortality inequalities in urban areas: a Bayesian small area analysis in Spanish cities
2011
incluye "Erratum to: Cancer mortality inequalities in urban areas: a Bayesian small area analysis in Spanish cities" BACKGROUND: Intra-urban inequalities in mortality have been infrequently analysed in European contexts. The aim of the present study was to analyse patterns of cancer mortality and their relationship with socioeconomic deprivation in small areas in 11 Spanish cities. METHODS: It is a cross-sectional ecological design using mortality data (years 1996-2003). Units of analysis were the census tracts. A deprivation index was calculated for each census tract. In order to control the variability in estimating the risk of dying we used Bayesian models. We present the RR of the censu…