scholarly journals On the recursive estimation of vehicular speed using data from a single inductance loop detector: A Bayesian approach

2009 ◽  
Vol 43 (4) ◽  
pp. 391-402 ◽  
Author(s):  
Baibing Li
Keyword(s):  
Bayesian Approach ◽  
Recursive Estimation ◽  
Loop Detector ◽  
Vehicular Speed ◽  
Using Data

Improving the Forecasting Process in Project Control

2014 ◽  
pp. 1173-1181
Author(s):  
Franco Caron
Keyword(s):  
Bayesian Approach ◽  
Future Development ◽  
Control Process ◽  
Knowledge Sources ◽  
Project Control ◽  
Forecasting Accuracy ◽  
Feed Forward Control ◽  
Using Data

In the project control process, the role of the ETC (Estimate to Complete) is critical, since, given a feed forward control loop, the only way to influence the overall project performance is to take actions affecting the work remaining. The forecasting accuracy related to ETC is linked to the ability of the project team to exploit all the knowledge available in order to anticipate the future development of the project. According to the classification of the knowledge sources it is possible to identify three different approaches to determining the ETC: (1) using data records related to the work completed by highlighting possible trends (2) adjusting the trend stemming from data records using experts' judgment and (3) integrating the internal view of the project, i.e. data records related to the work completed and experts' judgment related to work remaining, with data records deriving from similar projects completed in the past. A Bayesian approach may represent a possible way of integrating the different knowledge sources.

scholarly journals Bayesian approach to determining penetrance of pathogenic SDH variants

2018 ◽  
Vol 55 (11) ◽  
pp. 729-734 ◽  
Author(s):  
Diana E Benn ◽  
Ying Zhu ◽  
Katrina A Andrews ◽  
Mathilda Wilding ◽  
Emma L Duncan ◽  
...  
Keyword(s):  
Bayesian Approach ◽  
Genetic Variants ◽  
The Cancer Genome Atlas ◽  
Pathogenic Variants ◽  
Combining Data ◽  
Disease Penetrance ◽  
Cancer Genome Atlas ◽  
Observational Cohort ◽  
Using Data ◽  
Hereditary Pheochromocytoma

BackgroundUntil recently, determining penetrance required large observational cohort studies. Data from the Exome Aggregate Consortium (ExAC) allows a Bayesian approach to calculate penetrance, in that population frequencies of pathogenic germline variants should be inversely proportional to their penetrance for disease. We tested this hypothesis using data from two cohorts for succinate dehydrogenase subunits A, B and C (SDHA–C) genetic variants associated with hereditary pheochromocytoma/paraganglioma (PC/PGL).MethodsTwo cohorts were 575 unrelated Australian subjects and 1240 unrelated UK subjects, respectively, with PC/PGL in whom genetic testing had been performed. Penetrance of pathogenic SDHA–C variants was calculated by comparing allelic frequencies in cases versus controls from ExAC (removing those variants contributed by The Cancer Genome Atlas).ResultsPathogenic SDHA–C variants were identified in 106 subjects (18.4%) in cohort 1 and 317 subjects (25.6%) in cohort 2. Of 94 different pathogenic variants from both cohorts (seven in SDHA, 75 in SDHB and 12 in SDHC), 13 are reported in ExAC (two in SDHA, nine in SDHB and two in SDHC) accounting for 21% of subjects with SDHA–C variants. Combining data from both cohorts, estimated lifetime disease penetrance was 22.0% (95% CI 15.2% to 30.9%) for SDHB variants, 8.3% (95% CI 3.5% to 18.5%) for SDHC variants and 1.7% (95% CI 0.8% to 3.8%) for SDHA variants.ConclusionPathogenic variants in SDHB are more penetrant than those in SDHC and SDHA. Our findings have important implications for counselling and surveillance of subjects carrying these pathogenic variants.

Comparing Interval Restricted Estimators in Hedonic Pricing / Ein Vergleich intervallrestringierter Schätzverfahren in der hedonischen Preismessung

2000 ◽  
Vol 220 (5) ◽  
Author(s):  
Henning Knautz
Keyword(s):  
Monte Carlo ◽  
Bayesian Approach ◽  
Housing Prices ◽  
Hedonic Pricing ◽  
Monte Carlo Experiment ◽  
Constrained Estimation ◽  
Pricing Models ◽  
Interval Constraints ◽  
Using Data ◽  
Fuzzy Interval

SummaryIn hedonic pricing models there is often prior knowledge available which has the form of interval constraints on the unknown coefficients. These are stemming for example from considerations of submarkets for the characteristics involved. In this article we briefly discuss some well known estimators that allow for incorporation of this knowledge. Additionally we introduce two new promising approaches for the same purpose: a modified Bayesian approach and a method applying fuzzy interval constraints. Using data on housing prices we present the results of a Monte Carlo experiment in which these estimators are compared. It turns out that constrained estimation is promising especially in the situation of high multicollinearity and moderate R2 which is typical for hedonic pricing models. We illustrate that estimates and confidence intervals for the unknown coefficients can be improved substantially compared with the conventional unrestricted estimation.

scholarly journals Bayesian mapping of the striatal microcircuit reveals robust asymmetries in the probabilities and distances of connections

2021 ◽  
Author(s):  
Francois Cinotti ◽  
Mark D Humphries
Keyword(s):  
Bayesian Approach ◽  
D2 Receptor ◽  
Cognitive Disorders ◽  
Projection Neuron ◽  
Current Data ◽  
Projection Neurons ◽  
Range Of Movement ◽  
Precise Knowledge ◽  
Wide Range ◽  
Using Data

The striatum's complex microcircuit is made by connections within and between its D1- and D2-receptor expressing projection neurons and at least five species of interneuron. Precise knowledge of this circuit is likely essential to understanding striatum's functional roles and its dysfunction in a wide range of movement and cognitive disorders. We introduce here a Bayesian approach to mapping neuron connectivity using intracellular recording data, which lets us simultaneously evaluate the probability of connection between neuron types, the strength of evidence for it, and its dependence on distance. Using it to synthesise a complete map of the rodent striatum, we find strong evidence for two asymmetries: a selective asymmetry of projection neuron connections, with D2 neurons connecting twice as densely to other projection neurons than do D1 neurons, but neither subtype preferentially connecting to another; and a length-scale asymmetry, with interneuron connection probabilities remaining non-negligible at more than twice the distance of projection neuron connections. We further show our Bayesian approach can evaluate evidence for wiring changes, using data from the developing striatum and a mouse model of Huntington's disease. By quantifying the uncertainty in our knowledge of the microcircuit, our approach reveals a wide range of potential striatal wiring diagrams consistent with current data.

A Bayesian approach for estimating hexabromocyclododecane (HBCD) diastereomer compositions in water using data below limit of quantification

2016 ◽  
Vol 24 (3) ◽  
pp. 2667-2674 ◽  
Author(s):  
Makiko Ichihara ◽  
Atsushi Yamamoto ◽  
Naoya Kakutani ◽  
Miki Sudo ◽  
Koh-ichi Takakura
Keyword(s):  
Bayesian Approach ◽  
Limit Of Quantification ◽  
Using Data

Evaluation of the dynamic characteristics of a super tall building using data from ambient vibration and shake table tests by a Bayesian approach

2017 ◽  
Vol 25 (4) ◽  
pp. e2121 ◽  
Author(s):  
Feng-Liang Zhang ◽  
Carlos E. Ventura ◽  
Hai-Bei Xiong ◽  
Wen-Sheng Lu ◽  
Yu-Xin Pan ◽  
...  
Keyword(s):  
Bayesian Approach ◽  
Dynamic Characteristics ◽  
Tall Building ◽  
Ambient Vibration ◽  
Shake Table ◽  
Shake Table Tests ◽  
Using Data

A Bayesian Approach on Investigating Helicopter Emergency Medical Fatal Accidents

2021 ◽  
Vol 92 (7) ◽  
pp. 563-569
Author(s):  
Richard J. Simonson ◽  
Joseph R. Keebler ◽  
Alex Chaparro
Keyword(s):  
Bayesian Approach ◽  
Prior Information ◽  
Helicopter Emergency Medical Service ◽  
Current Data ◽  
Influential Factors ◽  
Fatal Accidents ◽  
Factors Associated ◽  
Emergency Medical ◽  
Accident Data ◽  
Using Data

INTRODUCTION: Helicopter Emergency Medical Service (HEMS) is a mode of transportation designed to expedite the transport of a patient. Compared to other modes of emergency transport and other areas of aviation, historically HEMS has had the highest accident-related fatality rates. Analysis of these accident data has revealed factors associated with an increased likelihood of accident-based fatalities. Here we report the results of an analysis on the likelihood of a fatality based on various factors as a result of a HEMS accident, employing a Bayesian framework.METHODS: A retrospective study was conducted using data extracted from the NTSB aviation accident database from April 31, 2005, to April 26, 2018. Evidence from Baker et al. (2006) was also used as prior information spanning from January 1, 1983, to April 30, 2005.RESULTS: A Bayesian logistic regression was implemented using the prior information and current data to calculate a posterior distribution confidence interval of possible values in predicting accident fatality. The results of the model indicate that flying at night (OR 3.06; 95 C.I 2.14, 4.48; PoD 100), flying under Instrument Flight Rules (OR 7.54; 95 C.I 3.94, 14.44; PoD 100), and post-crash fires (OR 18.73; 95 C.I 10.07, 34.12; PoD 100) significantly contributed to the higher likelihood of a fatality.CONCLUSION: Our results provide a comprehensive analysis of the most influential factors associated with an increased likelihood of a fatal accident occurring. We found that over the past 35 yr these factors were consistently associated with a higher likelihood of a fatality occurring.Simonson RJ, Keebler JR, Chaparro A. A Bayesian approach on investigating helicopter emergency medical fatal accidents. Aerosp Med Hum Perform. 2021; 92(7):563569.

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