Search results for "Bayesian statistics"
showing 10 items of 35 documents
The past and the present in decision-making: the use of conspecific and heterospecific cues in nest site selection
2014
International audience; Nest site selection significantly affects fitness, so adaptations for assessment of the qualities of available sites are expected. The assessment may be based on personal or social information, the latter referring to the observed location and performance of both conspecific and heterospecific individuals. Contrary to large-scale breeding habitat selection, small-scale nest site selection within habitat patches is insufficiently understood. We analyzed nest site selection in the migratory Collared Flycatcher Ficedula albicollis in relation to present and past cues provided by conspecifics and by resident tits within habitat patches by using long-term data. Collared F…
Potential of using data assimilation to support forest planning
2017
Uncertainty in forest information typically results in economic and ecological losses as a consequence of suboptimal management decisions. Several techniques have been proposed to handle such uncertainties. However, these techniques are often complex and costly. Data assimilation (DA) has recently been advocated as a tool that may reduce the uncertainty, thereby improving the quality of forest planning results. It offers an opportunity to make use of all new sources of information in a systematic way and thus provides more accurate and up-to-date information to forest planning. In this study, we refer to literature on handling uncertainties in forest planning, as well as related literature…
Importance of proper conduct of clinical trials
2021
Bayesian Methodology in Statistics
2009
Bayesian methods provide a complete paradigm for statistical inference under uncertainty. These may be derived from an axiomatic system and provide a coherent methodology which makes it possible to incorporate relevant initial information, and which solves many of the difficulties that frequentist methods are known to face. If no prior information is to be assumed, the more frequent situation met in scientific reporting, a formal initial prior function, the reference prior, mathematically derived from the assumed model, is used; this leads to objective Bayesian methods, objective in the precise sense that their results, like frequentist results, only depend on the assumed model and the data…
M.J. (Susie) Bayarri
2021
Finding Prediction Limits for a Future Number of Failures in the Prescribed Time Interval under Parametric Uncertainty
2012
Computing prediction intervals is an important part of the forecasting process intended to indicate the likely uncertainty in point forecasts. Prediction intervals for future order statistics are widely used for reliability problems and other related problems. In this paper, we present an accurate procedure, called ‘within-sample prediction of order statistics', to obtain prediction limits for the number of failures that will be observed in a future inspection of a sample of units, based only on the results of the first in-service inspection of the same sample. The failure-time of such units is modeled with a two-parameter Weibull distribution indexed by scale and shape parameters β and δ, …
Solving two‐armed Bernoulli bandit problems using a Bayesian learning automaton
2010
PurposeThe two‐armed Bernoulli bandit (TABB) problem is a classical optimization problem where an agent sequentially pulls one of two arms attached to a gambling machine, with each pull resulting either in a reward or a penalty. The reward probabilities of each arm are unknown, and thus one must balance between exploiting existing knowledge about the arms, and obtaining new information. The purpose of this paper is to report research into a completely new family of solution schemes for the TABB problem: the Bayesian learning automaton (BLA) family.Design/methodology/approachAlthough computationally intractable in many cases, Bayesian methods provide a standard for optimal decision making. B…
Radiocarbono y estadística Bayesiana: aportaciones a la cronología de la Edad del Bronce en el extremo oriental del sudeste de la península Ibérica
2014
La investigación arqueológica desarrollada en las últimas décadas ha permitido evaluar que en los valles de los ríos Segura y Vinalopó se dirimió el contacto entre dos sociedades de la Edad del Bronce de la península Ibérica: el grupo Argárico y el grupo del Prebético Meridional Valenciano. Las excavaciones realizadas en tres yacimientos de este ámbito - Terlinques, Cabezo Pardo y Cabezo Redondo- y las dotaciones de radiocarbono obtenidas permiten por primera vez evaluar la diacronía del proceso histórico que envolvió el desarrollo de ambos grupos arqueológicos a lo largo del II milenio cal BC, así como determinar diversos momentos socialmente significativos en su devenir histórico. Para el…
Estimation and visualization of confusability matrices from adaptive measurement data
2010
Abstract We present a simple but effective method based on Luce’s choice axiom [Luce, R.D. (1959). Individual choice behavior: A theoretical analysis. New York: John Wiley & Sons] for consistent estimation of the pairwise confusabilities of items in a multiple-choice recognition task with arbitrarily chosen choice-sets. The method combines the exact (non-asymptotic) Bayesian way of assessing uncertainty with the unbiasedness emphasized in the classical frequentist approach. We apply the method to data collected using an adaptive computer game designed for prevention of reading disability. A player’s estimated confusability of phonemes (or more accurately, phoneme–grapheme connections) and l…
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.