Bayesian model averaging (BMA)
Bayesian Model Averaging in the Studies on Economic Growth in the EU Regions – Application of the gretl BMA package
... the BMA (Bayesian Model Averaging) method a group of explanatory variables was proposed to determine potential factors responsible for differences in regional averages of GDP growth rate under ...
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Bayesian Model Averaging in the Instrumental Variable Regression Model
... huge model space, there are many problems with conventional model selection procedures ...problems). Bayesian model averaging (BMA) can be used to avoid some of these ...the ...
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Extended range Probabilistic 500hPa Geopotential Height Forecasting over Northern Hemisphere Using Bayesian Model Averaging
... the Bayesian model averaging (BMA) extended-range (10-15 days) probabilistic forecasts for 500hPa geopotential heights over Northern ...multimodel BMA method performed better than raw ...
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Bayesian Model Averaging: An Application to the Determinants of Airport Departure Delay in Uganda
... single model that could include all variables, but this proved to be inefficient and ...the Bayesian model averaging; BMA that took the problem through estimating models for all ...
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Robust Bayesian Filtering Using Bayesian Model Averaging and Restricted Variational Bayes
... Abstract —Bayesian filters can be made robust to outliers if the solutions are developed under the assumption of heavy-tailed distributed noise. However, in the absence of outliers, these robust solutions perform ...
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Prior Specification in Bayesian Model Averaging: An application to Economic Growth
... employed Bayesian Model Averaging to tackle the issue of model ...uncertainty. Bayesian model averaging has become an important tool in empirical settings with large ...
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The determinants of macroeconomic volatility: A Bayesian model averaging approach
... of Bayesian model averaging to the economics field have primarily been made in the empirical growth regression literature, due to the large number of possible determinants of growth with little ...
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Mixtures of g priors for Bayesian model averaging with economic applications
... subset. Bayesian Model Averaging presents a formal Bayesian solution to dealing with model ...on model size with a g-prior on the coefficients of each ...over model space ...
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Dam management with imperfect models: bayesian model averaging and neural network control
... dam. Bayesian model averaging is theoretically a good way to cope with these difficulties, but in practice it degrades under two approximations: discretizing the parameter space, and excluding models ...
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Bayesian Model Averaging and Identification of Structural Breaks in Time Series
... existing Bayesian literature on unit roots, and/or structural break test- ing has not adopted a conjugate normal gamma prior ...a Bayesian approach to structural break identi…cation using ...
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On the Effect of Prior Assumptions in Bayesian Model Averaging with Applications to Growth Regression
... For Bayesian (and approximately Bayesian) approaches to the problem, any differences can typically be interpreted as the use of different prior ...of BMA analyses—this general issue is also studied ...
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A Mixture Based Bayesian Model Averaging Method
... for BMA is now available for computational purposes; this package provides ways for carrying out BMA for linear regression, generalized linear models, and survival analysis using Cox proportional hazard ...
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Estimating the Output, Inflation and Unemployment Gaps in Ireland using Bayesian Model Averaging
... our model attributes a greater share of variance in the data to output gap movements, rather than potential output ...trivariate model average; in contrast, the comparable DG-ECFIN estimate is ...our ...
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The Determinants of Gini Coefficient in Iran Based on Bayesian Model Averaging
... Abstract: This paper has tried to apply BMA approach in order to investigate important influential variables on Gini coefficient in Iran over the period 1976-2010. The results indicate that the GDP growth is the ...
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Applying Bayesian model averaging for uncertainty estimation of input data in energy modelling
... whole model space, ...the BMA method, the uncertainty assessor firstly gathers any data that might be - even only in an indirect sense - be a relevant influence on the dependent ...The model space ...
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Model Uncertainty in Ecological Criminology: An Application of Bayesian Model Averaging With Rural Crime Data
... of BMA to take advantage of the information contained in as many models as ...single model with the highest posterior probability to determine which variables are to be further ...the BMA reduces to ...
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On the effect of prior assumptions in Bayesian model averaging with applications to growth regression
... For Bayesian (and approximately Bayesian) approaches to the problem, any differences can typically be interpreted as the use of different prior ...of BMA analyses. As BMA or similar approaches ...
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Development of a Regional Lidar-Derived Forest Inventory Model with Bayesian Model Averaging for use in Ponderosa Pine and Mixed Conifer Forests in Arizona and New Mexico, USA
... Figure 5. Scatter plot of field measured aboveground biomass versus predicted values from the raw biomass regression model (Table 6) for each of the plot sizes used in the study. Plot sizes for each window are: ...
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Learning Instance-Specific Predictive Models
... perform model selection. In model selection a single model is selected that summarizes the data well; it is then used to make future ...one model to the exclusion of all others, and this can ...
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Model Averaging in Markov Switching Models: Predicting National Recessions with Regional Data
... the model using Maryland employment data is high in the early part of the sample, whereas it is the model using data for the state of Virginia that gets the highest weight at the end of the sample (or the ...
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