Search results for "Bayesian probability"
showing 10 items of 217 documents
A Bayesian Learning Automaton for Solving Two-Armed Bernoulli Bandit Problems
2008
The 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. In the last decades, several computationally efficient algorithms for tackling this problem have emerged, with learning automata (LA) being known for their ?-optimality, and confidence interval based for logarithmically growing regret. Applications include treatment selection in clinical trials, route selection in …
Reply to Holliday and Boslough et al.: Synchroneity of widespread Bayesian-modeled ages supports Younger Dryas impact hypothesis
2015
Holliday (1) rejects age-depth models for the Younger Dryas boundary layer (YDB) in Kennett et al. (2), claiming that they are incorrect for several reasons, including age reversals, high age uncertainties, and use of optically stimulated luminescence (OSL) dating. These same claims previously were presented in Meltzer et al. (3) and were discussed and refuted in Kennett et al. (2). These criticisms apply to nearly all dated archaeological and geological sequences, including the Odessa meteorite impact crater, where paradoxically, Holliday et al. (4) modeled an impact age using OSL dating (>70% of dates used) with large uncertainties (to >6,000 y) and age reversals (>40% of dates are revers…
$\texttt{HEPfit}$: a Code for the Combination of Indirect and Direct Constraints on High Energy Physics Models
2020
The European physical journal / C Particles and fields C80(5), 456 (2020). doi:10.1140/epjc/s10052-020-7904-z
Strong Quantum Solutions in Conflicting Interest Bayesian Games
2017
Quantum entanglement has been recently demonstrated as a useful resource in conflicting-interest games of incomplete information between two players, Alice and Bob [Pappa et al., Phys. Rev. Lett. 114, 020401 (2015)]. The general setting for such games is that of correlated strategies where the correlation between competing players is established through a trusted common adviser; however, players need not reveal their input to the adviser. So far, the quantum advantage in such games has been revealed in a restricted sense. Given a quantum correlated equilibrium strategy, one of the players can still receive a higher than quantum average payoff with some classically correlated equilibrium str…
The Wage Curve, Once More with Feeling: Bayesian Model Averaging of Heckit Models
2018
The sensitivity of the wage curve to sample-selection and model uncertainty was evaluated with Bayesian methods. More than 8000 Heckit wage curves were estimated using data from the 2017 household survey of Bolivia. After averaging the estimates with the posterior probability of each model being true, the wage curve elasticity in Bolivia is close to -0.01. This result suggests that in this country the wage curve is inelastic and does not follow the international statistical regularity of wage curves.
On using novel “Anti-Bayesian” techniques for the classification of dynamical data streams
2017
The classification of dynamical data streams is among the most complex problems encountered in classification. This is, firstly, because the distribution of the data streams is non-stationary, and it changes without any prior “warning”. Secondly, the manner in which it changes is also unknown. Thirdly, and more interestingly, the model operates with the assumption that the correct classes of previously-classified patterns become available at a juncture after their appearance. This paper pioneers the use of unreported novel schemes that can classify such dynamical data streams by invoking the recently-introduced “Anti-Bayesian” (AB) techniques. Contrary to the Bayesian paradigm, that compare…
Inference and prediction in bulk arrival queues and queues with service in stages
1998
This paper deals with the statistical analysis from a Bayesian point of view, of bulk arrival queues where the batch size is considered as a fixed constant. The focus is on prediction of the usual measures of performance of the system in the steady state. The probability generating function of the posterior predictive distribution of the number of customers in the system and the Laplace transform of the posterior predictive distribution of the waiting time in the system are obtained. Numerical inversion of these transforms is considered. Inference and prediction of its equivalent single queue with service in stages is also discussed.
A Bayesian approach to assess data from radionuclide activity analyses in environmental samples
2007
A Bayesian statistical approach is introduced to assess experimental data from the analyses of radionuclide activity concentration in environmental samples (low activities). A theoretical model has been developed that allows the use of known prior information about the value of the measurand (activity), together with the experimental value determined through the measurement. The model has been applied to data of the Inter-laboratory Proficiency Test organised periodically among Spanish environmental radioactivity laboratories that are producing the radiochemical results for the Spanish radioactive monitoring network. A global improvement of laboratories performance is produced when this pri…
Bayesian Modelling of Confusability of Phoneme-Grapheme Connections
2007
Deficiencies in the ability to map letters to sounds are currently considered to be the most likely early signs of dyslexia. This has motivated the use of Literate, a computer game for training this skill, in several Finnish schools and households as a tool in the early prevention of reading disability. In this paper, we present a Bayesian model that uses a student's performance in a game like Literate to infer which phoneme-grapheme connections student currently confuses with each other. This information can be used to adapt the game to a particular student's skills as well as to provide information about the student's learning progress to their parents and teachers. We apply our model to …
Assessment of building energy modelling studies to meet the requirements of the new Energy Performance of Buildings Directive
2020
Abstract The cost optimal method (COM) as applied in the Energy Performance of Buildings Directive (EPBD) uses “non-calibrated deterministic reference buildings (RBs)”. Such RBs are defined with single envelope and equipment parameter values, for which calibration with actual building stock energy performance (EP) is not undertaken. Thus, it is not possible to visualise the effect of uncertainties or diversity in the input parameters on cost-optimal level benchmarks and to verify the choice of RBs. The paper proposes an update to the COM via use of “Probabilistic Bayesian calibrated RBs” to handle uncertainties and produce more realistic cost optimal levels to support policy makers in devis…