model averaging
Model averaging in economics
... on model averaging and growth are Fern´andez et ...Bayesian Averaging of Classical Estimates ...the model space with different prior expected model sizes (other papers applying these ...
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Frequentist Model Averaging and Applications to Bernoulli Trials
... Bayesian model averaging (BMA) and its variants, using Bayesian information criterion (BIC) as approximation (Schwarz ...perform model averaging on a set of nested candidate models with the ...
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A Review on High Dimensional Frequentist Model Averaging
... Model averaging has attracted increasing attention in recent years for the analysis of high-dimensional ...suitably, model averaging attempts to achieve stable and improved ...available ...
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Mixtures of g priors for Bayesian model averaging with economic applications
... Bayesian model explored in this paper has a hyperprior on the covariate inclusion probability θ and a hyperprior on g, which leads to an integral for the marginal likelihood that is solved by running the MCMC ...
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A Mixture Based Bayesian Model Averaging Method
... Bayesian model averaging (BMA) is a popular and powerful statistical method of taking account of uncertainty about model form or assumption. Usually the long run (frequentist) performances of the ...
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Prior Specification in Bayesian Model Averaging: An application to Economic Growth
... Bayesian Model Averaging to tackle the issue of model ...Bayesian model averaging has become an important tool in empirical settings with large numbers of potential regressors and ...
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World productivity growth: a model averaging approach
... of model averaging world productivity growth utilize both time invariant and time varying effects models to estimate innovation and effi- ciency ...panel model and to decompose T F P growth into a ...
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Bayesian Model Averaging and Identification of Structural Breaks in Time Series
... The BRs were derived using the model averaging procedures discussed in the preceding sections. The data generating process is as speci…ed in [1] with no breaks and one lag (and AR(1) with and without a ...
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The determinants of macroeconomic volatility: A Bayesian model averaging approach
... 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 theoretical ...
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Model selection and model averaging in nonparametric instrumental variables models
... proposed model selection criterion and model averaging criterion depend on unknown pop- ulation ...proposed model selection and model averaging estima- tors with other existing ...
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Essays on Robust Model Selection and Model Averaging for Linear Models
... Compared with other traditional model averaging methods, one main advantage of BLA is its computational feasibility in a high dimensional case where p > n. For a better illustration of the use of BLA ...
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Model Averaging for Prediction with Discrete Bayesian Networks
... probabilistic model accomplishes this goal by calculating the posterior proba- bility, P(C | F), of the class given the ...network model and no missing feature-vector data can be performed in O(N) ...single ...
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The Determinants of Gini Coefficient in Iran Based on Bayesian Model Averaging
... In both theoretical and empirical studies, many different kinds of variables have been considered as significant determinants of Gini coefficient. So in this research, by application of the method of Bayesian ...
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Model switching and model averaging in time-varying parameter regression models
... Bayesian model averaging or model selection (BMA or BMS) methods are commonly used when the researcher is faced with many ...regression model have enjoyed great popularity, particularly in ...
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New Criteria of Model Selection and Model Averaging in Linear Regression Models
... Model averaging is used to base point inferences on the entire set of models rather than a single best ...by model, sample size n=100, and regressors used in each ...by model, sample size ...
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Forecast Bitcoin Volatility with Least Squares Model Averaging
... squares model-averaging method. Unlike the model selection approach that picks only one winning model out of a pool of candidate models, model averaging calculates the weighted ...
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Model Switching and Model Averaging in Time-Varying Parameter Regression Models
... Bayesian model averaging or model selection (BMA or BMS) methods are commonly used when the researcher is faced with many ...regression model have enjoyed great popularity, particularly in ...
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Mixtures of g priors for Bayesian model averaging with economic applications
... 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 and ...
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Mixtures of g priors for Bayesian model averaging with economic applications
... Bayesian model explored in this paper has a hyperprior on the covariate inclusion probability θ and a hyperprior on g, which leads to an integral for the marginal likelihood that is solved by running the MCMC ...
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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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