Search results for "Probability."
showing 10 items of 3396 documents
Data Augmentation Approach in Bayesian Modelling of Presence-only Data
2011
Abstract Ecologists are interested in prediction of potential distribution of species in suitable areas, essential for planning conservation and management strategies. Unfortunately, often the only available information in such studies is the true presence of the species at few locations of the study area and the associated environmental covariates over the entire area, referred as presence-only data. We propose a Bayesian approach to estimate logistic linear regressions adapted to presence-only data through the introduction of a random approximation of the correction factor in the adjusted logistic model that allows us to overcome the need to know a priori the prevalence of the species.
Differences in Life Expectancy Between Self-Employed Workers and Paid Employees when Retirement Pensioners: Evidence from Spanish Social Security Rec…
2021
The aim of this paper is to examine differences in life expectancy (LE) between self-employed (SE) and paid employee (PE) workers when they become retirement pensioners, looking at levels of pension income using administrative data from Spanish social security records. We draw on the Continuous Sample of Working Lives (CSWL) to quantify changes in total life expectancy at age 65 (LE(65)) among retired men over the longest possible period covered by this data source: 2005–2018. These changes are broken down by pension regime and initial pension income level for three periods. The literature presents mixed evidence, even for the same country–for Japan and Italy, for example–with some studies …
Forest of Normalized Trees: Fast and Accurate Density Estimation of Streaming Data
2018
Density estimation of streaming data is a relevant task in numerous domains. In this paper, a novel non-parametric density estimator called FRONT (forest of normalized trees) is introduced. It uses a structure of multiple normalized trees, segments the feature space of the data stream through a periodically updated linear transformation and is able to adapt to ever evolving data streams. FRONT provides accurate density estimation and performs favorably compared to existing online density estimators in terms of the average log score on multiple standard data sets. Its low complexity, linear runtime as well as constant memory usage, makes FRONT by design suitable for large data streams. Final…
Comparing normal means: new methods for an old problem
2007
Comparing the means of two normal populations is an old problem in mathematical statistics, but there is still no consensus about its most appropriate solution. In this paper we treat the problem of comparing two normal means as a Bayesian decision problem with only two alternatives: either to accept the hypothesis that the two means are equal, or to conclude that the observed data are, under the assumed model, incompatible with that hypothesis. The combined use of an information-theory based loss function, the intrinsic discrepancy (Bernardo and Rueda 2002}, and an objective prior function, the reference prior \citep{Bernardo 1979; Berger and Bernardo 1992), produces a new solution to this…
Early stages of the acute physical stress response increase loss aversion and learning on decision making: A Bayesian approach
2021
Abstract When the cortisol peak is reached after a stressor people learn slower and make worse decisions in the Iowa Gambling Task (IGT). However, the effects of the early stress response have not received as much attention. Since physical exercise is an important neuroendocrine stressor, this study aimed to fill this gap using an acute physical stressor. We hypothesized that this stress stage would promote an alertness that may increase feedback-sensitivity and, therefore, reward-learning during IGT, leading to a greater overall decision-making. 90 participants were divided into two groups: 47 were exposed to an acute intense physical stressor (cycloergometer) and 43 to a distractor 5 min …
Multivariate Gaussian criteria in SMAA
2006
Abstract We consider stochastic multicriteria decision-making problems with multiple decision makers. In such problems, the uncertainty or inaccuracy of the criteria measurements and the partial or missing preference information can be represented through probability distributions. In many real-life problems the uncertainties of criteria measurements may be dependent. However, it is often difficult to quantify these dependencies. Also, most of the existing methods are unable to handle such dependency information. In this paper, we develop a method for handling dependent uncertainties in stochastic multicriteria group decision-making problems. We measure the criteria, their uncertainties and…
Probabilistic Logic under Coherence‚ Model−Theoretic Probabilistic Logic‚ and Default Reasoning in System P
2016
We study probabilistic logic under the viewpoint of the coherence principle of de Finetti. In detail, we explore how probabilistic reasoning under coherence is related to model-theoretic probabilistic reasoning and to default reasoning in System P. In particular, we show that the notions of g-coherence and of g-coherent entailment can be expressed by combining notions in model-theoretic probabilistic logic with concepts from default reasoning. Moreover, we show that probabilistic reasoning under coherence is a generalization of default reasoning in System P. That is, we provide a new probabilistic semantics for System P, which neither uses infinitesimal probabilities nor atomic bound (or bi…
Probabilistic Logic under Coherence, Model-Theoretic Probabilistic Logic, and Default Reasoning
2001
We study probabilistic logic under the viewpoint of the coherence principle of de Finetti. In detail, we explore the relationship between coherence-based and model-theoretic probabilistic logic. Interestingly, we show that the notions of g-coherence and of g-coherent entailment can be expressed by combining notions in model-theoretic probabilistic logic with concepts from default reasoning. Crucially, we even show that probabilistic reasoning under coherence is a probabilistic generalization of default reasoning in system P. That is, we provide a new probabilistic semantics for system P, which is neither based on infinitesimal probabilities nor on atomic-bound (or also big-stepped) probabil…
Bounds for the relative n-th nilpotency degree in compact groups
2009
The line of investigation of the present paper goes back to a classical work of W. H. Gustafson of the 1973, in which it is described the probability that two randomly chosen group elements commute. In the same work, he gave some bounds for this kind of probability, providing information on the group structure. We have recently obtained some generalizations of his results for finite groups. Here we improve them in the context of the compact groups.
Perpendicular transport properties of YBa_2Cu_3O_{7-\delta}/PrBa_2Cu_3O_{7-\delta} superlattices
2000
The coupling between the superconducting planes of YBa2Cu3O{7-\delta}/ PrBa2Cu3O{7-\delta} superlattices has been measured by c-axis transport. We show that only by changing the thickness of the superconducting YBa2Cu3O{7-\delta} layers, it is possible to switch between quasi-particle and Josephson tunneling. From our data we deduce a low temperature c-axis coherence length of 0.27 nm.