Results 11 to 20 of about 720,413 (297)
Model Uncertainty, State Uncertainty, and State-space Models [PDF]
SSRN Electronic Journal, 2013 State-space models have been increasingly used to study macroeconomic and financial problems. A state-space representation consists of two equations, a measurement equation which links the observed variables to unobserved state variables and a transition
Young, ER +5 more
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Formulating State Space Models in R with Focus on Longitudinal Regression Models
Journal of Statistical Software, 2006 We provide a language for formulating a range of state space models with response densities within the exponential family. The described methodology is implemented in the R-package sspir. A state space model is specified similarly to a generalized linear
Claus Dethlefsen +1 more
doaj +4 more sources
Journal of Statistical Software, 2011 We give an overview of some of the software tools available in R, either as built- in functions or contributed packages, for the analysis of state space models.
Giovanni Petris, Sonia Petrone
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Fitting State Space Models with EViews
Journal of Statistical Software, 2011 This paper demonstrates how state space models can be fitted in EViews. We first briefly introduce EViews as an econometric software package. Next we fit a local level model to the Nile data.
Filip A. M. Van den Bossche
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The STAMP Software for State Space Models
Journal of Statistical Software, 2011 This paper reviews the use of STAMP (Structural Time Series Analyser, Modeler and Predictor) for modeling time series data using state-space methods with unobserved components.
Roy Mendelssohn
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dynamichazard: Dynamic Hazard Models Using State Space Models
Journal of Statistical Software, 2021 The dynamichazard package implements state space models that can provide a computationally efficient way to model time-varying parameters in survival analysis. I cover the models and some of the estimation methods implemented in dynamichazard, apply them
Benjamin Christoffersen
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Predictive Control Based upon State Space Models [PDF]
Modeling, Identification and Control, 1989 Repetitive online computation of the control vector by solving the optimal control problem of a non-linear multivariable process with arbitrary performance indices is investigated.
Jens G. Balchen +2 more
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Wavelets in state space models [PDF]
Applied Stochastic Models in Business and Industry, 2003 AbstractIn this paper, we consider the utilization of wavelets in conjunction with state space models. Specifically, the parameters in the system matrix are expanded in wavelet series and estimated via the Kalman Filter and the EM algorithm. In particular this approach is used for switching models.
Zandonade, Eliana, Morettin, Pedro A.
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Bayesian State Space Models in Macroeconometrics [PDF]
SSRN Electronic Journal, 2020 AbstractState space models play an important role in macroeconometric analysis and the Bayesian approach has been shown to have many advantages. This paper outlines recent developments in state space modelling applied to macroeconomics using Bayesian methods.
Joshua C.C. Chan, Rodney W. Strachan
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CoRR, 2023 This paper studies sequence modeling for prediction tasks with long range dependencies. We propose a new formulation for state space models (SSMs) based on learning linear dynamical systems with the spectral filtering algorithm (Hazan et al. (2017)).
Naman Agarwal +3 more
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