Bayesian Framework for Updating Seismic Loss Functions with Limited Observational Data in Low-to-Moderate Seismicity Regions

2021 ◽  
pp. 1-24
Author(s):  
Insub Choi ◽  
JunHee Kim ◽  
WonHee Kang ◽  
Youngsuk Kim
Keyword(s):  
Observational Data ◽  
Bayesian Framework ◽  
Loss Functions ◽  
Seismic Loss ◽  
Moderate Seismicity

scholarly journals A 3-component mixture of inverse Rayleigh distributions: properties and estimation in Bayesian framework

2016 ◽  
Vol 5 (2) ◽  
pp. 120
Author(s):  
Tabasam Sultana ◽  
Muhammad Aslam
Keyword(s):  
Survival Analysis ◽  
Prior Information ◽  
Bayesian Framework ◽  
Reliability Theory ◽  
Statistical Properties ◽  
Loss Functions ◽  
Bayes Estimators ◽  
Informative Priors ◽  
Component Mixture ◽  
Censored Sampling

<p>This paper is about studying a 3-component mixture of the inverse Rayleigh distributions under Bayesian perspective. The censored sampling scheme is considered due to its popularity in reliability theory and survival analysis. The expressions for the Bayes estimators and their posterior risks are derived under different loss scenarios. In case, no little prior information is available, elicitation of hyper parameters is given. To examine, numerically, the performance of the Bayes estimators using non-informative and informative priors under different loss functions, we have simulated their statistical properties for different sample sizes and test termination times.</p>

Bayesian Machine Learning

2005 ◽  
pp. 229-235
Author(s):  
Eitel J.M. Lauria
Keyword(s):  
Machine Learning ◽  
Observational Data ◽  
Bayesian Methods ◽  
Posterior Probability ◽  
Prior Probability ◽  
Probabilistic Approach ◽  
Bayes Theorem ◽  
Bayesian Framework ◽  
Probability Models ◽  
Bayesian Machine Learning

Bayesian methods provide a probabilistic approach to machine learning. The Bayesian framework allows us to make inferences from data using probability models for values we observe and about which we want to draw some hypotheses. Bayes theorem provides the means of calculating the probability of a hypothesis (posterior probability) based on its prior probability, the probability of the observations and the likelihood that the observational data fit the hypothesis.

scholarly journals BISoN: A Bayesian Framework for Inference of Social Networks

2021 ◽  
Author(s):  
Jordan D. A. Hart ◽  
Michael N. Weiss ◽  
Daniel W. Franks ◽  
Lauren J. N. Brent
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Observational Data ◽  
Bayesian Framework ◽  
Social Data ◽  
Association Tests ◽  
Point Estimates ◽  
Network Properties

Social networks are often constructed from point estimates of edge weights. In many contexts, edge weights are inferred from observational data, and the uncertainty around point estimates can be affected by various factors. Though this has been acknowledged in previous work, methods that explicitly quantify uncertainty in edge weights have not yet been widely adopted, and remain undeveloped for common types of data. Furthermore, existing methods are unable to cope with some of the complexities often found in observational data, and do not propagate uncertainty in edge weights to subsequent analyses. We introduce a unified Bayesian framework for modelling social networks based on observational data. This framework, which we call BISoN, can accommodate many common types of observational social data, can capture confounds and model effects at the level of observations, and is fully compatible with popular methods of social network analysis. We show how the framework can be applied to common types of data and how various types of downstream analyses can be performed, including non-random association tests and regressions on network properties. Our framework opens up the opportunity to test new types of hypotheses, make full use of observational datasets, and increase the reliability of scientific inferences. We have made example R code available to enable adoption of the framework.

scholarly journals Simplified seismic loss functions for suspended ceilings and drywall partitions

2016 ◽  
Vol 49 (1) ◽  
pp. 64-78 ◽  
Author(s):  
Rajesh P. Dhakal ◽  
Atefeh Pourali ◽  
Sandip K. Saha
Keyword(s):  
Loss Function ◽  
Estimation Method ◽  
Loss Estimation ◽  
Loss Functions ◽  
Cumulative Distribution ◽  
Expected Loss ◽  
Financial Loss ◽  
Loss Assessment ◽  
Seismic Loss ◽  
The Cost

Post-disaster reconnaissance reports frequently list non-structural components (NSCs) as a major source of financial loss in earthquakes. Moreover, minimizing their damage is also of vital significance to the uninterrupted functionality of a building. For efficient decision making, it is important to be able to estimate the cost and downtime associated with the repair of the damage likely to be caused at different hazard levels used in seismic design. Generalized loss functions for two important NSCs commonly used in New Zealand, namely suspended ceilings and drywall partitions are developed in this study. The methodology to develop the loss functions, in the form of engineering demand parameter vs. expected loss due to the considered components, is based on the existing framework for the storey level loss estimation. Nevertheless, exhaustive construction/field data are employed to make these loss functions more generic. In order to estimate financial losses resulting from the failure of suspended ceilings, generalized ceiling fragility functions are developed and combined with the cost functions, which give the loss associated with typical ceilings at various peak acceleration demands. Similarly, probabilities of different damage states in drywall partitions are combined with their associated repair/replacement costs to find the cumulative distribution of the expected loss due to partitions at various drift levels, which is then normalized in terms of the total building cost. Efficiencies of the developed loss functions are investigated through detailed loss assessment of case study reinforced concrete (RC) buildings. It is observed that the difference between the expected losses for ceilings, predicted by the developed generic loss function, and the losses obtained from the detailed loss estimation method is within 5%. Similarly, the developed generic loss function for partitions is able to estimate the partition losses within 2% of that from the detailed loss assessment. The results confirm the accuracy of the proposed generic seismic loss functions.

Current status of special planetary and lunar theories and ephemerides

1966 ◽  
Vol 25 ◽  
pp. 266-267
Author(s):  
R. L. Duncombe
Keyword(s):  
Observational Data ◽  
Current Status ◽  
Numerical Errors

An examination of some specialized lunar and planetary ephemerides has revealed inconsistencies in the adopted planetary masses, the presence of non-gravitational terms, and some outright numerical errors. They should be considered of temporary usefulness only, subject to subsequent amendment as required for the interpretation of observational data.

July 11, 1991 Eclipse Corona Photometry by the Results of Electropolarimetric and CCD-Matrix Observations

1994 ◽  
Vol 144 ◽  
pp. 567-569
Author(s):  
V. Kulidzanishvili ◽  
D. Georgobiani
Keyword(s):  
Solar Corona ◽  
Observational Data ◽  
Solar Limb ◽  
Ccd Matrix

AbstractThe observational data of July 11, 1991 eclipse solar corona obtained by both electropolarimeter (EP) and CCD-matrix were processed. Using these data, the solar corona photometry was carried out. The results of EP data are compared with the ones of CCD data. It must be noted here that the CCD data give us only characteristics of the inner corona, while the EP data show the features of both the inner and middle corona up to 4R⊙. Standard flattening indexϵis evaluated from both data. The dependence of the flattening index on the distance from the solar limb is investigated. The isophotes in Na and Ca lines are plotted. Based on these data some ideas and conclusions on the type of the solar corona are presented.

On The Radii of Ap Stars

1976 ◽  
Vol 32 ◽  
pp. 49-55 ◽  
Author(s):  
F.A. Catalano ◽  
G. Strazzulla
Keyword(s):  
Observational Data ◽  
Line Width ◽  
Main Sequence ◽  
Main Sequence Stars ◽  
Ap Stars

SummaryFrom the analysis of the observational data of about 100 Ap stars, the radii have been computed under the assumption that Ap are main sequence stars. Radii range from 1.4 to 4.9 solar units. These values are all compatible with the Deutsch's period versus line-width relation.

Valence electron spectroscopy of inhomogeneous media

1992 ◽  
Vol 50 (2) ◽  
pp. 1150-1151
Author(s):  
A. Howie ◽  
D.W. McComb
Keyword(s):  
Specific Gravity ◽  
Loss Function ◽  
Electron Spectroscopy ◽  
Valence Electron ◽  
Peak Height ◽  
Loss Functions ◽  
Loss Peak ◽  
High Energies ◽  
Valence Electron Density ◽  
Electron Microscopist

The bulk loss function Im(-l/ε (ω)), a well established tool for the interpretation of valence loss spectra, is being progressively adapted to the wide variety of inhomogeneous samples of interest to the electron microscopist. Proportionality between n, the local valence electron density, and ε-1 (Sellmeyer's equation) has sometimes been assumed but may not be valid even in homogeneous samples. Figs. 1 and 2 show the experimentally measured bulk loss functions for three pure silicates of different specific gravity ρ - quartz (ρ = 2.66), coesite (ρ = 2.93) and a zeolite (ρ = 1.79). Clearly, despite the substantial differences in density, the shift of the prominent loss peak is very small and far less than that predicted by scaling e for quartz with Sellmeyer's equation or even the somewhat smaller shift given by the Clausius-Mossotti (CM) relation which assumes proportionality between n (or ρ in this case) and (ε - 1)/(ε + 2). Both theories overestimate the rise in the peak height for coesite and underestimate the increase at high energies.

Modeling Interstation Travel Speed of Hybrid Bus Rapid Transit within A Bayesian Framework

2019 ◽  
Vol 2 (5) ◽  
Author(s):  
Ji-hua Hu ◽  
Jia-xian Liang
Keyword(s):  
Road Traffic ◽  
Travel Speed ◽  
Bayesian Framework ◽  
Bus Rapid Transit ◽  
Rapid Transit ◽  
Important Indicator ◽  
Main Road ◽  
Traffic Lights ◽  
Speed Distribution ◽  
Hybrid Bus

Interstation travel speed is an important indicator of the running state of hybrid Bus Rapid Transit and passenger experience. Due to the influence of road traffic, traffic lights and other factors, the interstation travel speeds are often some kind of multi-peak and it is difficult to use a single distribution to model them. In this paper, a Gaussian mixture model charactizing the interstation travel speed of hybrid BRT under a Bayesian framework is established. The parameters of the model are inferred using the Reversible-Jump Markov Chain Monte Carlo approach (RJMCMC), including the number of model components and the weight, mean and variance of each component. Then the model is applied to Guangzhou BRT, a kind of hybrid BRT. From the results, it can be observed that the model can very effectively describe the heterogeneous speed data among different inter-stations, and provide richer information usually not available from the traditional models, and the model also produces an excellent fit to each multimodal speed distribution curve of the inter-stations. The causes of different speed distribution can be identified through investigating the Internet map of GBRT, they are big road traffic and long traffic lights respectively, which always contribute to a main road crossing. So, the BRT lane should be elevated through the main road to decrease the complexity of the running state.

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