Time-Varying Parameter Models
Variational Bayes inference in high dimensional time varying parameter models
... Regression models that incorporate stochastic variation in parameters have been used by economists at least since the works of Sarris (1973) and Cooley and Prescott ...that time-varying ...
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Time varying parameter models for catchments with land use change: the importance of model structure
... hydrologic models are parameterized to represent different possible future land use conditions ...cast models with hydrologic models ...in time, rather than assuming a constant optimal value ...
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Analysis of time varying parameter models
... reasonable choice of m there is a strong possibility that the transient actually occurred at time t . However the estimation of d, if d is greater than 1, is not easy. This should be done by trial and error ...
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Hierarchical Shrinkage in Time-varying Parameter Models
... of models with stochastic ...regression models without shrinkage and suggests the impor- tance of shrinkage such as that provided by the ...the models with stochastic volatility and focus on the ...
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Hierarchical shrinkage in time varying parameter models
... Table A.2: Forecast Performance for Overall Inflation: No Predictors Constant Variance Stochastic Volatility MLPL MSFE MAFE MLPL MSFE MAFE h=1 Lasso on constant and TVPs -0.50 0.66 0.79 [r] ...
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Brazilian foreign trade : fixed and time varying parameter models
... H., 1978, et alii "Econometric Modelling Time Series of the Aggregate Relationship Between Consumer's Expenditure and Income in the United Kingdom, The Economic Journal, 88,661-692.. Pol[r] ...
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A flexible approach to parametric inference in nonlinear and time varying time series models
... regime-switching models have been used with macroeconomic and …nancial ...nonlinear time series models, including those with regime-switching and structural ...from models exhibiting abrupt ...
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Time-varying Models for Macroeconomic Forecasts
... empirical parameter simulation using Bayesian methods, Chib and Greenberg (1994) develop a practical Markov chain Monte Carlo (MCMC) method that works well in low dimensions when resorting to the Kalman ...very ...
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Three Applications of Time-Varying Parameter and Stochastic Volatility Models to the Malaysian and Australian Economy
... A question that is left unanswered in Chapter 2 is Malaysia's monetary policy rule in regards to unexpected shocks to real GDP, ination and the Nominal Eective Exchange Rate. To investigate this issue further, one must ...
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Time varying dimension models
... Abstract: Time varying parameter (TVP) models have enjoyed an in- creasing popularity in empirical ...TVP models are parameter-rich and risk over-…tting unless the dimension of ...
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Efficient Estimation of the Parameter Path in Unstable Time Series Models
... the parameter path is useful for a number of ...the parameter path is useful for forecasting purposes (see, for instance, Chernoff and Zacks (1964), Sims (1993), Stock and Watson (1996) or Pesaran, Pet- ...
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Cosmological Models in Lyra Geometry with Linearly Varying Deceleration Parameter
... where k 1 0 and m 0 are constants. Here k 1 is a constant with the dimension of time inverse and m is a dimension free constant. This ansatz covers the rule for constant deceleration parameter presented ...
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Post-Regularization Inference for Time-Varying Nonparanormal Graphical Models
... graph G is a k-nearest neighbor graph for k ∈ {0, 2, 4, 8}. Here a k-nearest neighbor graph has edges only connecting a vertex to its closest k nodes. See Figure 1(a) for an illustration of a 4-nearest neighbor graph. ...
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Global End Use Demand for Cotton: A Time Varying Parameter Model
... Summary Allowing parameter estimates to vary through time for simple consumption models for the end-use of cotton confirmed some results from models with fixed parameters, and gave some [r] ...
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Real-time predictive control for SI engines using linear parameter-varying models
... The problem of engine torque and air-to-fuel ratio control is considered in this paper. The engine is the 2.4L engine used on a 2010 Chevy Equinox. Amongst the main characteristics of this particular engine are dual ...
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Sequential Parameter Estimation of Time Varying Non Gaussian Autoregressive Processes
... One advantage of particle filters over other methods is that they can be applied to almost any type of problem where signal variations are present. This includes models with high nonlinearities and with noises ...
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Identification of Nonlinear Parameter-Dependent Common-Structured models to accommodate varying experimental conditions and design parameter properties
... different parameter properties by best fitting all the data sets using the common structured model, with varying process internal ...conventional parameter-varying models, where process ...
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Identification of time-varying systems using multiresolution wavelet models
... The parameter vector θ in (40) can now be estimated using a least-squares-based algorithm or a prediction error routine (Billings and Voon ...nonlinear time varying ...
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Quasi Bayesian estimation of time varying volatility in DSGE models
... the parameter vector to include additional coe¢ cients from the latent volatility ...of time varying volatilities and time invariant parameters in a DSGE framework without imposing parametric ...
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Large time-varying parameter VARs
... over time and multivariate stochastic volatility is present (see, among many others, Cogley and Sargent, 2005, Cogley, Morozov and Sargent, 2005, Primiceri, 2005, Koop, Leon-Gonzalez and Strachan, 2009 and Canova ...
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