Introduction The basic idea of structural time series models is that they are set up as regression models in which the explanatory variables are functions of time with coefficients which change over time. Thus within a regression framework a simple trend would be modeled in terms of a constant ...
Introduction The basic idea of structural time series models is that they are set up as regression models in which the explanatory variables are functions of time with coefficients which change over time. Thus within a regression framework a simple trend would be modeled in terms of a constant ...
Structural Time Series ModelsThe basic idea of structural time series models is that they are set up as regression models in which the explanatory variables are functions of time with coefficients which change over time. Thus...doi:10.1007/978-3-642-04898-2_577Abril, Juan Carlos...
1989. Forecasting, Structural Time Series Models, and the Kalman Filter. Cambridge University Press: Cambridge, UK and New York, NY... AC Harvey - John Wiley & Sons, Ltd 被引量: 556发表: 2005年 Forecasting Economic Time Series with Structural and Box-Jenkins Models: A Case Study: Comment...
This paper introduces the class of seasonal specific structural time series models, ac- cording to which each season follows specific dynamics, but is also tied to the others by a common random eects. This results in a dynamic variance components model that can account for some kind of periodi...
The use of a structural time series approach allows an attempt to model the underlying dynamics of productivity growth jointly with the effect of unemployment. 展开 关键词: Unemployment Manycountries Economic models Time series Studies Economic growth Productivity ...
Lee, Bong-Soo and Beth Fisher Ingram, "Simulation Estimation of Time Series Models", Journal of Econometrics, 47:2-3, pp. 197-205 (February 1991). McFadden, Daniel, "A Method of Simulated Moments for Estimation of Discrete Response Models without Numerical Integration," Econometrica, 57:5, ...
Causal impact analysis of weir opening on cyanobacterial blooms and water quality in the Yeongsan River, Korea: A bayesian structural time-series analysis ... Assessing environmental event impact is challenging due to confounding factors.Bayesian structural time-series models provide insights into weir ...
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Causal inference using Bayesian structural time-series models. This package aims at defining a python equivalent of theR CausalImpact package by Google. Please refer tothe packageitself,its documentationor therelated publication(Brodersen et al., Annals of Applied Statistics, 2015) for more information...