Search results for "Bayesian [statistical analysis]"

Estimating finite mixtures of semi-Markov chains: an application to the segmentation of temporal sensory data

2019

Summary In food science, it is of great interest to obtain information about the temporal perception of aliments to create new products, to modify existing products or more generally to understand the mechanisms of perception. Temporal dominance of sensations is a technique to measure temporal perception which consists in choosing sequentially attributes describing a food product over tasting. This work introduces new statistical models based on finite mixtures of semi-Markov chains to describe data collected with the temporal dominance of sensations protocol, allowing different temporal perceptions for a same product within a population. The identifiability of the parameters of such mixtur…

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…

Strategies for Improving Optimal Positioning of Quality Sensors in Urban Drainage Systems for Non-Conservative Contaminants

2021

In the urban drainage sector, the problem of polluting discharges in sewers may act on the proper functioning of the sewer system, on the wastewater treatment plant reliability and on the receiving water body preservation. Therefore, the implementation of a chemical monitoring network is necessary to promptly detect and contain the event of contamination. Sensor location is usually an optimization exercise that is based on probabilistic or black-box methods and their efficiency is usually dependent on the initial assumption made on possible eligibility of nodes to become a monitoring point. It is a common practice to establish an initial non-informative assumption by considering all network…

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…

A Bayesian spatio‐temporal analysis of markets during the Finnish 1860s famine

2022

We develop a Bayesian spatio-temporal model to study pre-industrial grain market integration during the Finnish famine of the 1860s. Our model takes into account several problematic features often present when analysing multiple spatially interdependent time series. For example, compared with the error correction methodology commonly applied in econometrics, our approach allows simultaneous modelling of multiple interdependent time series avoiding cumbersome statistical testing needed to predetermine the market leader as a point of reference. Furthermore, introducing a flexible spatio-temporal structure enables analysing detailed regional and temporal dynamics of the market mechanisms. Appl…

Insights into the derivative-based method for nonlinear mediation models

2022

Associational mediation analysis has generally relied on the linearity of models to estimate the indirect effect as a product of regression coefficients. Very few examples of generalisations to nonlinear settings have been proposed, including a derivative-based method that, however, is far from being widely spread among scholars. In this paper, we clarify some aspects of such an approach to nonlinear mediation models, which have not been addressed by the previous literature. In addition, we run a simulation study to compare confidence intervals for the indirect effect obtained through different approaches.

Data from: Extinction and recolonization of maritime Antarctica in the limpet Nacella concinna (Strebel, 1908) during the last glacial cycle: toward …

2013

Quaternary glaciations in Antarctica drastically modified geographical ranges and population sizes of marine benthic invertebrates and thus affected the amount and distribution of intraspecific genetic variation. Here, we present new genetic information in the Antarctic limpet Nacella concinna, a dominant Antarctic benthic species along shallow ice-free rocky ecosystems. We examined the patterns of genetic diversity and structure in this broadcast spawner along maritime Antarctica and from the peri-Antarctic island of South Georgia. Genetic analyses showed that N. concinna represents a single panmictic unit in maritime Antarctic. Low levels of genetic diversity characterized this population…

Mathematical Modeling for Neuropathic Pain: Bayesian Linear Regression and Self-Organizing Maps Applied to Carpal Tunnel Syndrome

2020

A better understanding of the connection between risk factors associated with pain and function may assist therapists in optimizing therapeutic programs. This study applied mathematical modeling to analyze the relationship of psychological, psychophysical, and motor variables with pain, function, and symptom severity using Bayesian linear regressions (BLR) and self-organizing maps (SOMs) in carpal tunnel syndrome (CTS). The novelty of this work was a transfer of the symmetry mathematical background to a neuropathic pain condition, whose symptoms can be either unilateral or bilateral. Duration of symptoms, pain intensity, function, symptom severity, depressive levels, pinch tip grip force, a…

Prostate Cancer Segmentation from Multiparametric MRI Based on Fuzzy Bayesian Model

2014

International audience

Ecologists overestimate the importance of predictor variables in model averaging: a plea for cautious interpretations.

2014

Abstract: Information-theory procedures are powerful tools for multimodel inference and are now standard methods in ecology. When performing model averaging on a given set of models, the importance of a predictor variable is commonly estimated by summing the weights of models where the variable appears, the so-called sum of weights (SW). However, SWs have received little methodological attention and are frequently misinterpreted. We assessed the reliability of SW by performing model selection and averaging on simulated data sets including variables strongly and weakly correlated to the response variable and a variable unrelated to the response. Our aim was to investigate how useful SWs are …