Structural Time Series Models
Short Term Forecasting of Bicycle Traffic Using Structural Time Series Models
... flow models may be developed by using theoretical techniques based on traffic process theory or by using empirical techniques which employ statistical and/or heuristic ...include time series ...
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Analysis of a cross section of time series using structural time series models
... 1 ANALYSIS OF A CROSS SECTION OF TIME SERIES USING STRUCTURAL TIME SERIES MODELS by Pablo Marshall Rivera London School of Economics and Political Science 1990 Submitted to the University of London fo[.] ...
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Non Gaussian structural time series models
... b y fixing its first two moments it is possible to solve numerically for a t and f3t , and therefore, fully specify the prior-posterior analysis together with the predictive moments for y t . It is obvious that for this ...
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Structural Time Series Models for Business Cycle Analysis
... The simulation smoother is an algorithm which draws samples from the conditional distribution of the states and the disturbances given the observations and the hyperparameters. Carlin, Pol- son and Stoffer (1992) ...
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Prediction of Traffic Related Nitrogen Oxides Concentrations using Structural Time Series Models
... a Structural Time Series (STS) based approach has been introduced in this paper to develop a parsimonious and computationally simple air quality ...a time-series dataset such as the ...
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Bayesian inference for nonlinear structural time series models
... biological models with intractable transition ...rational-expectations models with high signal-to-noise ratios when compared to the standard particle filter and the filter in Murray et ...
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Robust estimation for structural time series models
... Let us first consider the series with only additive outliers , i.e. g=100 , b = l . The scale , namely , o £ and a are estimated as 1.05 and 0.91 respectively by the AGSF while the Kalman filter’s estimates are ...
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Beyond location and dispersion models: The Generalized Structural Time Series Model with Applications
... flexible structural time series modelling frame- work for the estimation, analysis and forecasting of the dynamic behaviour of univariate time series ...erent structural ...
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Flattening of the Phillips Curve and the Role of Oil Price: An Unobserved Components Model for the USA and Australia
... Previous studies have concentrated only on changes in the coefficient of the output gap (GAP) and neglected changes in the intercept and coefficients of other variables. This paper includes oil prices as an additional ...
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Multivariate Bayesian Structural Time Series Model
... correlated time series, where one also has the choice of using a candidate pool of contemporaneous predictors for each target ...a structural model for time series, we use Bayesian ...
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Some aspects of estimation for vector time series models
... different models and because of the non-linear nature of the likelihood equa tions this requirement could impose a large computational ...scalar time series models, although it has its origin ...
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Inflation Analysis: An Overview
... forecasts. Structural models are, however, useful in clarifying the relationships among the key macroeconomic variables which determine the rate of inflation and consequently provide a framework within ...
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Long memory and structural breaks in time series models
... examines structural breaks in time series regressions where both regressors and errors may exhibit long range ...estimating structural breaks are analysed and asymptotic distribution of ...
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Dating structural changes in time series: The case of the Moroccan macroeconomic series
... of structural econometric models. Currently, all models are developed for a stationary ...with structural breaks ...the series have undergone at least two breaks (two structural ...
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Econometrics and truth
... STRUCTURAL MODELS AND TIME SERIES ECONOMETRICS BEFORE COINTEGRATION The principal difference between the application of statistics to economics and to other sciences arises from the non-[r] ...
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Techniques for short term economic forecasting
... Assuming correct specification and exogenous variable assumptions, structural econometric models should produce more accurate forecasts than multivariate time series methods.. This arise[r] ...
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Estimation and identification for vector linear time series models
... The models discussed in the thesis have useful empirical applications (prediction, control, structural analysis) in Engineering and Econometrics, although it may sometimes be necessary to transform the ...
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Univariate Time Series Models For Fuel Price
... of time series assumes just as great importance in the study of every single one economic ...Fuzzy Time Series (FTS), Double Exponential Smoothing (DES) model and Auto Regressive Integrated ...
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Selection of Heteroscedastic Models: A Time Series Forecasting Approach
... (1,1)-norm models for the banks ...the models se- lected through in-sample criteria are ...heteroscedastic models of return series of diamond ...
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Detecting instabilities in tree-ring proxy calibration
... As for initial values of noise variances we have chosen the approach of a so-called diffuse or non-informative prior. This means that we set the initial covariance matrix to the unity matrix with large numbers on the ...
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