Search results for "Probability."
showing 10 items of 3396 documents
Measurements of baryon pair decays of chi(cJ) mesons
2013
Using 106 $\times 10^{6}$ $\psi^{\prime}$ decays collected with the BESIII detector at the BEPCII, three decays of $\chi_{cJ}$ ($J=0,1,2$) with baryon pairs ($\llb$, $\ssb$, $\SSB$) in the final state have been studied. The branching fractions are measured to be $\cal{B}$$(\chi_{c0,1,2}\rightarrow\Lambda\bar\Lambda) =(33.3 \pm 2.0 \pm 2.6)\times 10^{-5}$, $(12.2 \pm 1.1 \pm 1.1)\times 10^{-5}$, $(20.8 \pm 1.6 \pm 2.3)\times 10^{-5}$; $\cal{B}$$(\chi_{c0,1,2}\rightarrow\Sigma^{0}\bar\Sigma^{0})$ = $(47.8 \pm 3.4 \pm 3.9)\times 10^{-5}$, $(3.8 \pm 1.0 \pm 0.5)\times 10^{-5}$, $(4.0 \pm 1.1 \pm 0.5) \times 10^{-5}$; and $\cal{B}$$(\chi_{c0,1,2}\rightarrow\Sigma^{+}\bar\Sigma^{-})$ = $(45.4 \pm…
Λ(1520)andΣ(1385)in the nuclear medium
2006
Recent studies of the {lambda}(1520) resonance within chiral unitary theory with coupled channels find the resonance as a dynamically generated state from the interaction of the decuplet of baryons and the octet of mesons, essentially a quasibound state of {pi}{sigma}{sup *}(1385) in this case, although the coupling of the {lambda}(1520) to the KN and {pi}{sigma} makes this picture only approximate. The {pi}{sigma}{sup *}(1385) decay channel of the {lambda}(1520) is forbidden in free space for the nominal mass of the {sigma}{sup *}(1385), but the coupling of the {pi} to ph components in the nuclear medium opens new decay channels of the {lambda}(1520) in the nucleus and produces a much larg…
Practical Issues on Energy-Growth Nexus Data and Variable Selection With Bayesian Analysis
2018
Abstract Given that the energy-growth nexus (EGN) is short of a complete theoretical base, the production function used therein is typically complemented with numerous variables that characterize an economy. Researchers are often puzzled not only with the selection of variables per se, but also with the variable sources and the various data handlings which become apparent and available only after years of experience in this research field. Thus, this chapter is divided into two distinctive parts: The first part contains an overview of the available data sources for the EGN as well as a succinct selection of advice on data handlings, transformations, and interpretations that could come handy…
On incorporating the paradigms of discretization and Bayesian estimation to create a new family of pursuit learning automata
2013
Published version of an article in the journal: Applied Intelligence. Also available from the publisher at: http://dx.doi.org/10.1007/s10489-013-0424-x There are currently two fundamental paradigms that have been used to enhance the convergence speed of Learning Automata (LA). The first involves the concept of utilizing the estimates of the reward probabilities, while the second involves discretizing the probability space in which the LA operates. This paper demonstrates how both of these can be simultaneously utilized, and in particular, by using the family of Bayesian estimates that have been proven to have distinct advantages over their maximum likelihood counterparts. The success of LA-…
Rejection odds and rejection ratios: A proposal for statistical practice in testing hypotheses
2016
Much of science is (rightly or wrongly) driven by hypothesis testing. Even in situations where the hypothesis testing paradigm is correct, the common practice of basing inferences solely on p-values has been under intense criticism for over 50 years. We propose, as an alternative, the use of the odds of a correct rejection of the null hypothesis to incorrect rejection. Both pre-experimental versions (involving the power and Type I error) and post-experimental versions (depending on the actual data) are considered. Implementations are provided that range from depending only on the p-value to consideration of full Bayesian analysis. A surprise is that all implementations -- even the full Baye…
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…
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…
Choosing Optimal Seed Nodes in Competitive Contagion.
2019
International audience; In recent years there has been a growing interest in simulating competitive markets to find out the efficient ways to advertise a product or spread an ideology. Along this line, we consider a binary competitive contagion process where two infections, A and B, interact with each other and diffuse simultaneously in a network. We investigate which is the best centrality measure to find out the seed nodes a company should adopt in the presence of rivals so that it can maximize its influence. These nodes can be used as the initial spreaders or advertisers by firms when two firms compete with each other. Each node is assigned a price tag to become an initial advertiser whi…
Enchytraeid population dynamics: Resource limitation and size-dependent mortality
2009
Abstract Enchytraeids are regarded as keystone soil organisms in forest ecosystems. Their abundance and biomass fluctuate widely. Predicting the consequences of anthropogenic disturbances requires an understanding of the mechanisms underlying enchytraeid population dynamics. Here I develop a simple model, which predicts that the type of dynamics is controlled by resource input rate. If fungal resource input is a discrete event once a year, an exponential growth phase is followed by starvation and sharp decline of enchytraeid abundance. Model simulations with three different forcing functions were compared to field data. Initial parameter values were obtained from various independent sources…