Relevant bibliographies by topics / Fractional Bayes factor

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  1. Journal articles
  2. Dissertations / Theses
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  4. Book chapters
  5. Conference papers

Academic literature on the topic 'Fractional Bayes factor'

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Published: 9 March 2023
Last updated: 10 March 2023

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Journal articles on the topic "Fractional Bayes factor"

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Conigliani, Caterina, and Anthony O'hagan. "Sensitivity of the fractional Bayes factor to prior distributions." Canadian Journal of Statistics 28, no. 2 (June 2000): 343–52. http://dx.doi.org/10.2307/3315983.

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De Santis, Fulvio, and Fulvio Spezzaferri. "Consistent fractional Bayes factor for nested normal linear models." Journal of Statistical Planning and Inference 97, no. 2 (September 2001): 305–21. http://dx.doi.org/10.1016/s0378-3758(00)00240-8.

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Dittrich, Dino, Roger Th A. J. Leenders, and Joris Mulder. "Network Autocorrelation Modeling: A Bayes Factor Approach for Testing (Multiple) Precise and Interval Hypotheses." Sociological Methods & Research 48, no. 3 (October 12, 2017): 642–76. http://dx.doi.org/10.1177/0049124117729712.

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Currently available (classical) testing procedures for the network autocorrelation can only be used for falsifying a precise null hypothesis of no network effect. Classical methods can be neither used for quantifying evidence for the null nor for testing multiple hypotheses simultaneously. This article presents flexible Bayes factor testing procedures that do not have these limitations. We propose Bayes factors based on an empirical and a uniform prior for the network effect, respectively, first. Next, we develop a fractional Bayes factor where a default prior is automatically constructed. Simulation results suggest that the first two Bayes factors show superior performance and are the Bayes factors we recommend. We apply the recommended Bayes factors to three data sets from the literature and compare the results to those coming from classical analyses using p values. R code for efficient computation of the Bayes factors is provided.
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Ariza-Hernandez, Francisco J., Jorge Sanchez-Ortiz, Martin P. Arciga-Alejandre, and Luis X. Vivas-Cruz. "Bayesian Analysis for a Fractional Population Growth Model." Journal of Applied Mathematics 2017 (2017): 1–9. http://dx.doi.org/10.1155/2017/9654506.

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We implement the Bayesian statistical inversion theory to obtain the solution for an inverse problem of growth data, using a fractional population growth model. We estimate the parameters in the model and we make a comparison between this model and an exponential one, based on an approximation of Bayes factor. A simulation study is carried out to show the performance of the estimators and the Bayes factor. Finally, we present a real data example to illustrate the effectiveness of the method proposed here and the pertinence of using a fractional model.
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de Santis, Fulvio, and Fulvio Spezzaferri. "Methods for Default and Robust Bayesian Model Comparison: The Fractional Bayes Factor Approach." International Statistical Review / Revue Internationale de Statistique 67, no. 3 (December 1999): 267. http://dx.doi.org/10.2307/1403706.

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Santis, Fulvio, and Fulvio Spezzaferri. "Methods for Default and Robust Bayesian Model Comparison: the Fractional Bayes Factor Approach." International Statistical Review 67, no. 3 (December 1999): 267–86. http://dx.doi.org/10.1111/j.1751-5823.1999.tb00449.x.

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Mashayekhi, Somayeh, and Peter Beerli. "Fractional coalescent." Proceedings of the National Academy of Sciences 116, no. 13 (March 13, 2019): 6244–49. http://dx.doi.org/10.1073/pnas.1810239116.

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An approach to the coalescent, the fractional coalescent (f-coalescent), is introduced. The derivation is based on the discrete-time Cannings population model in which the variance of the number of offspring depends on the parameter α. This additional parameter α affects the variability of the patterns of the waiting times; values ofα<1lead to an increase of short time intervals, but occasionally allow for very long time intervals. Whenα=1, the f-coalescent and the Kingman’s n-coalescent are equivalent. The distribution of the time to the most recent common ancestor and the probability that n genes descend from m ancestral genes in a time interval of length T for the f-coalescent are derived. The f-coalescent has been implemented in the population genetic model inference software Migrate. Simulation studies suggest that it is possible to accurately estimate α values from data that were generated with known α values and that the f-coalescent can detect potential environmental heterogeneity within a population. Bayes factor comparisons of simulated data withα<1and real data (H1N1 influenza and malaria parasites) showed an improved model fit of the f-coalescent over the n-coalescent. The development of the f-coalescent and its inclusion into the inference program Migratefacilitates testing for deviations from the n-coalescent.
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Kaiser, Andrew R., Nihan S. Pol, Maura A. McLaughlin, Siyuan Chen, Jeffrey S. Hazboun, Luke Zoltan Kelley, Joseph Simon, Stephen R. Taylor, Sarah J. Vigeland, and Caitlin A. Witt. "Disentangling Multiple Stochastic Gravitational Wave Background Sources in PTA Data Sets." Astrophysical Journal 938, no. 2 (October 1, 2022): 115. http://dx.doi.org/10.3847/1538-4357/ac86cc.

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Abstract With strong evidence of a common-spectrum stochastic process in the most recent data sets from the NANOGrav Collaboration, the European Pulsar Timing Array (PTA), Parkes PTA, and the International PTA, it is crucial to assess the effects of the several astrophysical and cosmological sources that could contribute to the stochastic gravitational wave background (GWB). Using the same data set creation and injection techniques as in Pol et al., we assess the separability of multiple GWBs by creating single and multiple GWB source data sets. We search for these injected sources using Bayesian PTA analysis techniques to assess recovery and separability of multiple astrophysical and cosmological backgrounds. For a GWB due to supermassive black hole binaries and an underlying weaker background due to primordial gravitational waves with a GW energy-density ratio of ΩPGW/ΩSMBHB = 0.5, the Bayes’ factor for a second process exceeds unity at 17 yr, and increases with additional data. At 20 yr of data, we are able to constrain the spectral index and amplitude of the weaker GWB at this density ratio to a fractional uncertainty of 64% and 110%, respectively, using current PTA methods and techniques. Using these methods and findings, we outline a basic protocol to search for multiple backgrounds in future PTA data sets.
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O'Hagan, Anthony. "Fractional Bayes Factors for Model Comparison." Journal of the Royal Statistical Society: Series B (Methodological) 57, no. 1 (January 1995): 99–118. http://dx.doi.org/10.1111/j.2517-6161.1995.tb02017.x.

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O’Hagan, A. "Properties of intrinsic and fractional Bayes factors." Test 6, no. 1 (June 1997): 101–18. http://dx.doi.org/10.1007/bf02564428.

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Dissertations / Theses on the topic "Fractional Bayes factor"

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Wang, Guojun. "Some Bayesian Methods in the Estimation of Parameters in the Measurement Error Models and Crossover Trial." University of Cincinnati / OhioLINK, 2004. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1076852153.

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ARTARIA, ANDREA. "Objective Bayesian Analysis for Differential Gaussian Directed Acyclic Graphs." Doctoral thesis, Università degli Studi di Milano-Bicocca, 2014. http://hdl.handle.net/10281/55327.

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Often we are confronted with heterogeneous multivariate data, i.e., data coming from several categories, and the interest may center on the differential structure of stochastic dependence among the variables between the groups. The focus in this work is on the two groups problem and is faced modeling the system through a Gaussian directed acyclic graph (DAG) couple linked in a fashion to obtain a joint estimation in order to exploit, whenever they exist, similarities between the graphs. The model can be viewed as a set of separate regressions and the proposal consists in assigning a non-local prior to the regression coefficients with the objective of enforcing stronger sparsity constraints on model selection. The model selection is based on Moment Fractional Bayes Factor, and is performed through a stochastic search algorithm over the space of DAG models.
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Garnier, Gérard. "Le facteur B du complément humain : bases structurales et biosynthétiques de sa microhétérogénéité, mises en évidence par les techniques électrophorétiques." Rouen, 1988. http://www.theses.fr/1988ROUES026.

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Palazzoli, Irene. "Identification of the most effective factors responsible for the flushing of a tracer in a system of shallow bays." Thesis, 2017. https://hdl.handle.net/2144/24086.

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The exchange of dissolved constituents between a shallow bay and the ocean is governed by regular tidal fluxes as well as by wind generated storm surges and currents. In this study the transport of a conservative tracer was simulated using the numerical model Delft3D in a system of shallow bays along the coast of the Delmarva Peninsula, Virginia. The evaluation of the tracer residence time was carried out using the Eulerian approach. The main mechanisms governing the decay of the tracer concentration inside the lagoons were assessed by considering the influence of different factors such as the time of release of the tracer with respect to the tidal cycle, tidal amplitude, and local winds. The exponential curve well approximates the decay of the tracer concentration in time. A set of simulations shows that the prevailing factor controlling the tracer transport and, therefore, the tracer concentration within the lagoons are wind-driven fluxes. Large tidal amplitudes also promote the flushing of the tracer out of the bay, while the time of tracer release with respect to the tidal phase has been found to play a relatively negligible role. Finally, a simplified approach is presented to compute the decay of tracer concentration in time. The method accounts for hourly variable wind characteristics as well as seasonal changes in meteorological conditions.
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Books on the topic "Fractional Bayes factor"

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Reutenauer, Christophe. From Christoffel Words to Markoff Numbers. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198827542.001.0001.

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Christoffel introduced in 1875 a special class of words on a binary alphabet, linked to continued fractions. Some years laterMarkoff published his famous theory, called nowMarkoff theory. It characterizes certain quadratic forms, and certain real numbers by extremal inequalities. Both classes are constructed by using certain natural numbers, calledMarkoff numbers; they are characterized by a certain diophantine equality. More basically, they are constructed using certain words, essentially the Christoffel words. The link between Christoffelwords and the theory ofMarkoffwas noted by Frobenius.Motivated by this link, the book presents the classical theory of Markoff in its two aspects, based on the theory of Christoffel words. This is done in Part I of the book. Part II gives the more advanced and recent results of the theory of Christoffel words: palindromes (central words), periods, Lyndon words, Stern–Brocot tree, semi-convergents of rational numbers and finite continued fractions, geometric interpretations, conjugation, factors of Christoffel words, finite Sturmian words, free group on two generators, bases, inner automorphisms, Christoffel bases, Nielsen’s criterion, Sturmian morphisms, and positive automorphisms of this free group.
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Book chapters on the topic "Fractional Bayes factor"

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De Santis, Fulvio, and Fulvio Spezzaferri. "Comparing hierarchical models using Bayes factor and fractional Bayes factor: a robust analysis." In Institute of Mathematical Statistics Lecture Notes - Monograph Series, 305–14. Hayward, CA: Institute of Mathematical Statistics, 1996. http://dx.doi.org/10.1214/lnms/1215453075.

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Moreno, Elias. "Bayes factors for intrinsic and fractional priors in nested models. Bayesian robustness." In Institute of Mathematical Statistics Lecture Notes - Monograph Series, 257–70. Hayward, CA: Institute of Mathematical Statistics, 1997. http://dx.doi.org/10.1214/lnms/1215454142.

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Habyarimana, Ephrem, and Sofia Michailidou. "Genomic Prediction and Selection in Support of Sorghum Value Chains." In Big Data in Bioeconomy, 207–18. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-71069-9_16.

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AbstractGenomic prediction and selection models (GS) were deployed as part of DataBio project infrastructure and solutions. The work addressed end-user requirements, i.e., the need for cost-effectiveness of the implemented technologies, simplified breeding schemes, and shortening the time to cultivar development by selecting for genetic merit. Our solutions applied genomic modelling in order to sustainably improve productivity and profits. GS models were implemented in sorghum crop for several breeding scenarios. We fitted the best linear unbiased predictions data using Bayesian ridge regression, genomic best linear unbiased predictions, Bayesian least absolute shrinkage and selection operator, and BayesB algorithms. The performance of the models was evaluated using Monte Carlo cross-validation with 70% and 30%, respectively, as training and validation sets. Our results show that genomic models perform comparably with traditional methods under single environments. Under multiple environments, predicting non-field evaluated lines benefits from borrowing information from lines that were evaluated in other environments. Accounting for environmental noise and other factors, also this model gave comparable accuracy with traditional methods, but higher compared to the single environment model. The GS accuracy was comparable in genomic selection index, aboveground dry biomass yield and plant height, while it was lower for the dry mass fraction of the fresh weight. The genomic selection model performances obtained in our pilots are high enough to sustain sorghum breeding for several traits including antioxidants production and allow important genetic gains per unit of time and cost.
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Cnossen, Sijbren. "Revenue Performance." In Modernizing VATs in Africa, 62–76. Oxford University Press, 2019. http://dx.doi.org/10.1093/oso/9780198844075.003.0006.

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Chapter 6 examines the revenue performance of African VATs by calculating their collection efficiencies defined as actual VAT revenue as a fraction of potential revenue. The VAT gap consists of the policy gap (exemptions and reduced rates) and the compliance gap (evasion and lack of enforcement). Possible explanatory factors, such as the level of economic development, the VAT structure, and the effectiveness of the VAT administration, are reviewed. The analysis appears to indicate that it is unlikely that African VATs in their current form are up to the task of generating much more revenue. Further, replacement of trade taxes by VATs is not easy if VAT bases are too narrow and enforcement too shallow to put much trust in VAT’s revenue-raising capacity.
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Del Genio, Anthony D. "GCM Simulations of Cirrus for Climate Studies." In Cirrus. Oxford University Press, 2002. http://dx.doi.org/10.1093/oso/9780195130720.003.0019.

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One of the great challenges in predicting the rate and geographical pattern of climate change is to faithfully represent the feedback effects of various cloud types that arise via different mechanisms in different parts of the atmosphere. Cirrus clouds are a particularly uncertain component of general circulation model (GCM) simulations of long-term climate change for a variety of reasons, as detailed below. First, cirrus encompass a wide range of optical thicknesses and altitudes. At one extreme are the thin tropopause cirrus that barely affect the short-wave albedo while radiating to space at very cold temperatures, producing a net positive effect on the planetary radiation balance and causing local upper troposphere warming, thus stabilizing the lapse rate. At the other extreme are thick cumulus anvil cirrus whose bases descend to the freezing level; these clouds produce significant but opposing short-wave and long-wave effects on the planetary energy balance while cooling the surface via their reflection of sunlight. In fact, satellite climatologies show a continuum of optical thicknesses between these two extremes (Rossow and Schiffer 1991). In a climate change, the net effect of cirrus might either be a positive or a negative feedback, depending on the sign and magnitude of the cloud cover change in each cloud-type category and the direction and extent of changes in their optical properties (see Stephens et al. 1990). Second, the dynamic processes that create cirrus are poorly resolved and different in different parts of the globe. In the tropics, small-scale convective transport of water from the planetary boundary layer to the upper troposphere is the immediate source of a significant fraction of the condensate in mesoscale cirrus anvils (see Gamache and Houze 1983), and ultimately the source of much of the water vapor that condenses out in large-scale uplift to form thinner cirrus. However, many observed thin cirrus cannot directly be identified with a convective source, suggesting that in situ upper troposphere dynamics and regeneration processes within cirrus (see Starr and Cox 1985) are important. In mid-latitudes, although summertime continental convection is a source of cirrus, in general cirrus is associated with mesoscale frontal circulations in synoptic-scale baroclinic waves and jet streaks (see Starr and Wylie 1990; Mace et al. 1995).
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Conference papers on the topic "Fractional Bayes factor"

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Al-Ali, Mohannad H., and K. C. Ho. "Bayesian multi-antenna sensing in cognitive radio networks using Fractional Bayes Factor." In 2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, 2017. http://dx.doi.org/10.1109/icassp.2017.7952822.

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Botsis, Ch, G. Anagnostides, and N. Kokavesis. "A Comprehensive Review of Ultimate and Allowable Stress Design Methodologies for External Load Calculation of Petrochemical Equipment: Eurocode 8 Versus ASME Codes." In ASME 2003 Pressure Vessels and Piping Conference. ASMEDC, 2003. http://dx.doi.org/10.1115/pvp2003-2108.

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The purpose of this paper is to provide a review of design methodologies for process equipment under pressure subjected to seismic loads. Such equipment includes spherical and cylindrical tanks, pressure vessels including towers and reactors, and fired heaters. For this equipment, the wall thickness of the pressure retaining space is designed so that the hoop stress is a fraction of the yield stress, Sy, of the material of construction. This fraction of the yield stress is called the allowable stress, Sm, and it is used in the allowable stress design codes such as ASME and API. However the magnitude of the stresses due to external loads is not determined by code rules. The task of calculating the stresses due to external loads is left up to the designer. Furthermore, process equipment is often sufficiently massive so that anchorage is needed to avoid overturning and a potential fire hazard. The anchors or bolts are imbedded in concrete bases, which are designed using strength design codes such as UBC, ASCE or EUROCODES. The level of stress in such structures is allowed to reach the yield stress of the material of construction. The safety factor in structures sized using allowable stress design philosophy is taken in the allowable stress. The safety factor in structures sized using strength design philosophy is realized by using load factors or increased loads. Guidelines are provided to solve the problem of merging the two design philosophies while avoiding the application of safety factors twice in the mechanical design of process equipment subjected to external loads and pressure.
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Zha, Kan, Radu-Catalin Florea, and Marcis Jansons. "Comparison of Soot Evolution Using High-Speed CMOS Color Camera and Two-Color Thermometry in an Optical Diesel Engine Fueled With B20 Biodiesel Blend and Ultra-Low Sulfur Diesel." In ASME 2011 Internal Combustion Engine Division Fall Technical Conference. ASMEDC, 2011. http://dx.doi.org/10.1115/icef2011-60146.

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Biodiesel is a desirable alternative fuel for the diesel engine due to its low engine-out soot emission tendency. When blended with petroleum-based diesel fuels, soot emissions generally decrease in proportion to the volume fraction of biodiesel in the mixture. While comparisons of engine-out soot measurements between biodiesel blends and petroleum-based diesel have been widely reported, in-cylinder soot evolution has not been experimentally explored to the same extent. To elucidate the soot emission reduction mechanism of biodiesel, a single-cylinder optically-accessible diesel engine was used to compare the in-cylinder soot evolution when fueled with ultra-low sulfur diesel (ULSD) to that using a B20 biodiesel blend (20% vol/vol biodiesel ASTM D6751-03A). Soot temperature and KL factors are simultaneously determined using a novel two-color optical thermometry technique implemented with a high-speed CMOS color camera having wide-band Bayer filters. The crank-angle resolved data allows quantitative comparison of the rate of in-cylinder soot formation. High-speed spray images show that B20 has more splashing during spray wall impingement than ULSD, distributing rebounding fuel droplets over a thicker annular ring interior to the piston bowl periphery. The subsequent soot luminescence is observed by high-speed combustion imaging and soot temperature and KL factor measurements. B20 forms soot both at low KL magnitudes over large areas between fuel jets, and at high values among remnants of the fuel spray, along its axis and away from the bowl edge. In contrast, ULSD soot luminescence is observed exclusively as pool burning on the piston bowl surfaces resulting from fuel wall impingement. The soot KL factor evolution during B20 combustion indicates earlier and significantly greater soot formation than with ULSD. B20 combustion is also observed to have a greater soot oxidation rate which results in lower engine-out soot emissions. Measured soot temperatures near 1875K were similar for the two fuels for the duration of combustion. For both fuels, higher fuel injection pressure led to lower late-cycle soot KL levels. The trends of soot natural luminosity correlated well with the trends of soot KL factor, suggesting that relatively simple measurements of combustion luminosity may provide somewhat quantitative information about in-cylinder soot formation and oxidation. The apparent rate of heat release (ARHR) analysis under steady skip-fire conditions indicates that B20 combustion is less sensitive to wall temperature than that observed with ULSD due to a lesser degree of pool burning. B20 was found to have both a shorter ignition delay and shorter combustion duration than ULSD.
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Glaude, Pierre A., Rene´ Fournet, Roda Bounaceur, and Michel Moliere. "Gas Turbines and Biodiesel: A Clarification of the Relative NOX Indices of FAME, Gasoil, and Natural Gas." In ASME Turbo Expo 2009: Power for Land, Sea, and Air. ASMEDC, 2009. http://dx.doi.org/10.1115/gt2009-59623.

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There is currently a sustained interest in biofuels as they represent a potential alternative to petroleum derived fuels. Biofuels are likely to help decrease greenhouse gases emissions and the dependence on oil resources. Biodiesels are Fatty Acid Methyl Esters (FAMEs) that are mainly derived from vegetable oils; their compositions depend from the parent vegetables: rapeseed (“RME”), soybean (“SME”), sunflower, palm etc. A fraction of biodiesel has also an animal origin (“tallow”). A key factor for the use of biofuels in gas turbines is their Emissions Indices (NOx, CO, VOC, PM) in comparison with those of conventional “petroleum gasoils”. While biodiesels reduce carbon-containing pollutants, experimental data from diesel engines show a slight increase in NOx. The literature relating to gas turbines is very scarce. Two recent, independent field tests carried out in Europe (RME) and in the USA (SME) showed slightly lower NOx while a lab test on a microturbine showed the opposite effect. To clarify the NOx index of biodiesels in gas turbines, a study has been undertaken, taking gasoil and natural gas (NG) as reference fuels. In this study, a calculation of the flame temperature developed by the 3 classes of fuels has been performed and the effect of their respective compositions has been investigated. The five FAMEs studied were RME, SME and methyl esters of sunflower, palm and tallow; these are representative of most widespread vegetable and animal oil bases worldwide. The software THERGAS has been used to calculate the enthalpy and free energy properties of the fuels and GASEQ for the flame temperature (Tf), acknowledging the fact that “thermal NOx” represents the predominant form of NOx in gas turbines. To complete the approach to structural effects, we have modeled two NG compositions (rich and weak gas) and three types of gasoil using variable blends of eleven linear/branched/cyclic molecules. The results are consistent with the two recent field tests and show that the FAMEs lie close to petroleum gasoils and higher than NG in terms of NOx emission. The composition of the biodiesel and regular diesel fuel influences their combustion heat: methyl esters with double bonds see a slight increase of their Tf and their NOx index while that of gasoil is sensitive to the aromatic content.
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Corporan, Edwin, Matthew J. DeWitt, Christopher D. Klingshirn, Shannon M. Mahurin, and Meng-Dawn Cheng. "Emissions Characteristics of a Legacy Military Aircraft." In ASME Turbo Expo 2009: Power for Land, Sea, and Air. ASMEDC, 2009. http://dx.doi.org/10.1115/gt2009-59255.

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Emissions from aircraft and associated ground equipment are major sources of local pollution at airports and military bases. These pollutant emissions, especially particulate matter (PM), have been receiving significant attention lately due to their proven harmful health and environmental effects. As the U.S. Environmental Protection Agency (EPA) tightens environmental standards, it is likely that military operations, including the basing of advanced and legacy aircraft, will be impacted. Accurate determination of emission indices from aircraft is necessary to properly assess their environmental burden. As such, the gaseous and PM emissions of a B-52 Stratofortress aircraft were characterized in this effort. This emissions study supports the Strategic Environmental Research and Development Program (SERDP) project WP-1401 to determine emissions factors from military aircraft. The main purpose of the project is to develop a comprehensive emissions measurement program using both conventional and advanced techniques to determine emissions factors for pollutants of fixed and rotating wing military aircraft. Standard practices for the measurement of gaseous emissions from aircraft have been well established; however, there is no certified methodology for the measurement of aircraft PM emissions. In this study, several conventional aerosol instruments were employed to physically characterize the PM emissions from two of the aircraft’s TF33 turbofan engines. Exit plane pollutant emissions were extracted via probes and transported through heated lines to the analytical instruments. Particle concentrations, size distributions and mass emissions, as well as engine smoke numbers (SN), soot volatile fraction and total hydrocarbon emissions were measured. The engines were tested at four power settings, from idle to 75% normal rated thrust (NRT) (95% N2 – turbine speed). Test results show relatively consistent PM and gaseous emissions between the two engines for most conditions tested. The measured TF33 PM mass emission indices (EI), including estimated sampling line losses, were in the range of 1.0–3.0 g/kg-fuel and the particle number (PN) EI were between 4.0–10.0E+15 particles/kg-fuel. The particle size data followed a single mode lognormal distribution for all power settings with particle geometric mean diameters ranging from 52 to 85 nm. In general, the aerosol instrumentation provided consistent and reliable measurements throughout the test campaign, therefore increasing confidence on their use for turbine engine PM emissions measurements.
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