[PDF] Top 20 Bayesian Model Selection and Forecasting in Noncausal Autoregressive Models
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Bayesian Model Selection and Forecasting in Noncausal Autoregressive Models
... on noncausal AR models is not voluminous, and so far very few economic applications ...a noncausal AR specification for the ...on noncausal AR and related models in statistics only ... See full document
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Forecasting bubbles with mixed causal noncausal autoregressive models
... for forecasting MAR(r,1) models, with unconstrained r number of lags, a unique lead and a positive lead ...causal- noncausal autoregressive ...based forecasting approach proposed by ... See full document
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Forecasting bubbles with mixed causal noncausal autoregressive models
... MAR models to predict both explosive and stable episodes remains scarce (see also Lanne, Nyberg, and Saarinen, 2012 and Gouri´eroux, Hencic, and Jasiak, ...for forecasting MAR(r,1) models, with ... See full document
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Bayesian analysis of random coefficient autoregressive models
... RCAR(1) model to the original ...lower forecasting limits (denoted by triangles) fall below zero; Also, the long term forecasting interval seems to converge very ...to model the ... See full document
35
Dynamic staged trees for discrete multivariate time series : forecasting, model selection and causal analysis
... steady model has a long history with Dirichlet distributions ...in Bayesian forecasting under the alternative name of exponential forgetting (Raftery et ...steady model as a justifiable and ... See full document
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Bayesian and Frequentist Approach to Time Series Forecasting with Application to Kenya’s GDP per Capita
... the Bayesian approaches to Kenya’s GDP per capita time series data for the period between 1980-2017 as obtained from the World Bank data ...The autoregressive integrated moving average (ARIMA) and the state ... See full document
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Frequentist and Bayesian Analysis of Random Coefficient Autoregressive models
... the model, e.g., for a RCA(1) model d = 4 whereas for a AR(1) model d = ...for models with random coefficients it is not clear if the penalty function should only depend on d as defined ...true ... See full document
146
Model selection, estimation and forecasting in INAR(p) models: A likelihood-based Markov Chain approach
... considers model selection, estimation and forecasting for a class of integer autoregressive models suitable for use when analysing time series count ...methods. Model ... See full document
22
Detecting Co Movements in Noncausal Time Series
... and noncausal vector autoregressive (VAR) ...for forecasting accuracy, parameter efficiency as well as for the interpretation of business cycle co-movements and the evaluation of economic theories ... See full document
25
Forecasting Chinese inflation and output: A Bayesian vector autoregressive approach
... several Bayesian vector autoregressive (VAR) models for forecasting price inflation and output growth in ...that models with shrinkage and model selection priors, that ... See full document
10
Modeling Expectations with Noncausal Autoregressions
... for noncausal autoregressive ...potentially noncausal autoregressive ...causal autoregressive model by least squares or Gaussian ML and determine its or- der by using ... See full document
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Optimal Forecasting of Noncausal Autoregressive Time Series
... reestimated models at each step with the estimation sample always starting from the …rst quarter of ...purely noncausal …fth-order AR models as well as the AR(1,4) model selected for the ... See full document
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Bayesian analysis of cointegrated vector autoregressive models
... In this chapter we deal with testing for multiple structural breaks in a vector error correction model as a problem of model selection and approximate the Bayes factors by Schwarz's Baye[r] ... See full document
144
Noncausal autoregressions for economic time series
... Univariate autoregressive models are commonly employed in characterizing the dy- namics of economic time ...include forecasting and the measurement of persistence (Andrews and Chen (1994)), but also ... See full document
40
Bayesian Expectations and Strategic Complementarity: Implications for Macroeconomic Stability
... macroeconomic model with Bayesian ...has Bayesian expectations with additional abilities to ...with Bayesian expectations mitigates the price persistence since the proportion of naive agents ... See full document
13
Forecasting Annual International Tourist Arrivals in Zambia Using Holt Winters Exponential Smoothing
... the forecasting performance of SARIMA, Holt Win- ters and Grey model for foreign tourist arrivals series in India from 2003:1 - 2015:10 using error ...the forecasting accuracy of Grey model ... See full document
10
Forecasting in dynamic factor models using Bayesian model averaging
... Τηε υσε οφ τηε πριορσ οϖερ mοδελ σπαχε γιϖεν ιν 3.10 ανδ τηε 99.9% πριορ ε¤εχτιϖελψ ρυλε ουτ mοστ οφ τηε φαχτορσ ασσοχιατεδ ωιτη σmαλλ ειγενϖαλυεσ ανδ, ηενχε, τηε mαργιναλ λικελιηοοδ ρεσ[r] ... See full document
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Discount Bayesian models and forecasting
... EWR by Brown the that method proposed cannot achieve a Mean Absolute showed Deviation MAD of less than 3% since it insists upon using a single inadequate discount factor in a case in whi[r] ... See full document
117
Multivariate Bayesian forecasting models
... is given in Section 2.1, the updating recursions are provided in Sction 2.2, time invariant interpretation of the parameters and model building from simple components are the topics in S[r] ... See full document
128
Forecasting Using Functional Coefficients Autoregressive Models
... parametric models for forecasting economic time series is widespread among practitioners, in spite of the fact that there is a large evidence of the presence of non-linearities in many of such time ... See full document
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