Search results for "Bayesian Inference"
showing 10 items of 120 documents
Optimizing channel selection for cognitive radio networks using a distributed Bayesian learning automata-based approach
2015
Consider a multi-channel Cognitive Radio Network (CRN) with multiple Primary Users (PUs), and multiple Secondary Users (SUs) competing for access to the channels. In this scenario, it is essential for SUs to avoid collision among one another while maintaining efficient usage of the available transmission opportunities. We investigate two channel access schemes. In the first model, an SU selects a channel and sends a packet directly without Carrier Sensing (CS) whenever the PU is absent on this channel. In the second model, an SU invokes CS in order to avoid collision among co-channel SUs. For each model, we analyze the channel selection problem and prove that it is a so-called "Exact Potent…
Flexible Bayesian survival models with application in biometric studies
2018
El análisis de supervivencia es una metodología estadística diseñada para analizar datos procedentes de estudios científicos relativos a tiempos de ocurrencia de uno o varios eventos de interés. La duración de estos tiempos suele conocerse como tiempos de supervivencia debido a los particulares orígenes de esta metodología en contextos exclusivamente médicos y demográficos. Durante las últimas décadas, la literatura científica en este campo ha sido muy prolífica y su aplicación se ha extendido a múltiples áreas de conocimiento. Los procedimientos estadísticos propios de esta metodología empezaron a abordarse desde el marco inferencial frecuentista. Sin embargo, en los últimos años la utiliz…
Consistency of Probability Decision Rules and Its Inference in Probability Decision Table
2012
In most synthesis evaluation systems and decision-making systems, data are represented by objects and attributes of objects with a degree of belief. Formally, these data can be abstracted by the form (objects; attributes; P), wherePrepresents a kind degree of belief between objects and attributes, such that,Pis a basic probability assignment. In the paper, we provide a kind of probability information system to describe these data and then employ rough sets theory to extract probability decision rules. By extension of Dempster-Shafer evidence theory, we can get probabilities of antecedents and conclusion of probability decision rules. Furthermore, we analyze the consistency of probability de…
Accelerated Bayesian learning for decentralized two-armed bandit based decision making with applications to the Goore Game
2012
Published version of an article in the journal: Applied Intelligence. Also available from the publisher at: http://dx.doi.org/10.1007/s10489-012-0346-z The two-armed bandit problem is a classical optimization problem where a decision maker sequentially pulls one of two arms attached to a gambling machine, with each pull resulting in a random reward. The reward distributions are unknown, and thus, one must balance between exploiting existing knowledge about the arms, and obtaining new information. Bandit problems are particularly fascinating because a large class of real world problems, including routing, Quality of Service (QoS) control, game playing, and resource allocation, can be solved …
What drives German foreign direct investment? New evidence using Bayesian statistical techniques
2019
Abstract Despite the importance of Germany as an issuer of foreign direct investment (FDI), the studies analyzing its determinants are far from conclusive. This research contributes to filling this gap providing new evidence for the period 1996–2012. In order to reduce model uncertainty, we adopt a Bayesian model averaging (BMA) approach. We find that determinants associated with horizontal FDI appear to be dominant for explaining FDI in developed countries while for the group of developing countries covariates associated with vertical FDI motives play a larger role. Within Europe, while the majority of FDI is horizontally driven in “core” countries, in the “periphery” vertical motivations …
Ethics of Beliefs
2017
This paper deals with the concept of positive learning (PL). The main goal is to provide a working definition of PL on which further refinements and extensions can be based. First, I formulate a list of desiderata for a definition of PL: I argue that a working definition of PL should (i) make the involved epistemic norms explicit, (ii) be flexible, and (iii) be empirically tractable. After that, I argue that a working definition of PL should focus on three basic epistemic norms (which I call Evidentialism, Degrees of Plausibility, and Non-Arbitrary Updates). Drawing on work on the ethics of belief and Bayesian inference, I highlight theoretical and empirical challenges that already follow f…
A BMA Analysis to Assess the Urbanization and Climate Change Impact on Urban Watershed Runoff
2016
Abstract A reliable planning of urban drainage systems aimed at the mitigation of flooding, should take into account the possible change over time of impervious cover in the urban watershed and of the climate features. The present study proposes a methodology to analyze the changing in runoff response for a urban watershed accounting several plausible future states of new urbanization and climate. To this aim, several models simulating the evolution scenario of impervious watershed area and of climate change were adopted. However, it is known that an evolution scenario represents only one of all possible occurrence and it is not necessary the true future state, therefore it is needed to fin…
Spatial Bayesian Modeling Applied to the Surveys of Xylella fastidiosa in Alicante (Spain) and Apulia (Italy)
2020
The plant-pathogenic bacterium Xylella fastidiosa was first reported in Europe in 2013, in the province of Lecce, Italy, where extensive areas were affected by the olive quick decline syndrome, caused by the subsp. pauca. In Alicante, Spain, almond leaf scorch, caused by X. fastidiosa subsp. multiplex, was detected in 2017. The effects of climatic and spatial factors on the geographic distribution of X. fastidiosa in these two infested regions in Europe were studied. The presence/absence data of X. fastidiosa in the official surveys were analyzed using Bayesian hierarchical models through the integrated nested Laplace approximation (INLA) methodology. Climatic covariates were obtained from …
Statistical methods for adaptive river basin management and monitoring
2018
Decision-making at different phases of adaptive river basin management planning rely largely on the information that is gained through environmental monitoring. The aim of this thesis was to develop and test statistical assessment tools presumed to be particularly useful for evaluating existing monitoring designs, converting monitoring data into management information and quantifying uncertainties. River basin scale monitoring was performed using a wireless sensor network and a data quality control system and maintenance effort was assessed. National-scale, traditional monitoring data and linear mixed effect modelling were used to estimate the uncertainty in two status class metrics (total …
Causal Models for Monitoring University Ordinary Financing Fund
2012
Recently iterated decreasing government transfers and an increasing proportion of budget allotted basing on competitive performances, took Italian Universities started struggling with competition for funds, in particular for the University Ordinary Financing Fund (FFO). Aim of this paper is monitoring variables responsible for FFO indicators, where monitoring means: describing, analysing retrospectively, predicting and intervening on variables responsible for indicators. All this aims can be achieved by statistical techniques that should be theoretically equipped with the distinction between predicting under observation and predicting under intervention, in order to provide correct answers …