In this paper, Hamilton's (1988, 1989) Markov-switching model is extended to a general state-space model. This paper also complements Shumway and Stoffer's (1991) dynamic linear models with switching, by introducing dependence in the switching process, and by allowing switching in both ...
Dynamic linear models with Markov-switching Journal of Econometrics (1994) W.K. Newey et al. Large sample estimation and hypothesis testingView more references Cited by (213) Forecasting: theory and practice 2022, International Journal of Forecasting Show abstract Financialization, crisis and commodity...
This model class covers finite mixture modeling, Markov switching autoregressive modeling, and dynamic linear models with switching. The consequences the unidentifiability of this type of model has on Markov chain Monte Carlo (MCMC) estimation are explicitly dealt with. Joint Bayesian estimation of all...
Gibbs sampling approach to regime switching analysis of financial time series We will introduce a Monte Carlo type inference in the framework of Markov Switching models to analyse financial time series, namely theGibbs Sampling. In p... LD Persio,M Frigo - 《Journal of Computational & Applied Ma...
python machine-learning hmm time-series dtw multivariate knn dynamic-time-warping sequence-classification hidden-markov-models sequential-patterns time-series-classification multivariate-timeseries variable-length classification-algorithms k-nearest-neighbor-classifier Updated Dec 30, 2024 Python Gordon...
To estimate the time frame of the information processing involved in behavioral transitions, we analyzed behavioral sequences using Markov chain models. The modeling revealed that accounting for preceding behaviors did not improve predictions about the upcoming one (Extended Data Fig.2a). This suggested...
Addressing the interconnectedness of oil prices and foreign exchange rates poses a substantial challenge and raises significant questions within economic research. Existing studies reveal a fragmented understanding of the dynamics between these crucial v
In particular, we propose a novel method that allows for time-varying sparsity, based on an extension of spike-and-slab priors for dynamic models. This is done by assigning appropriate Markov switching priors for the time-varying coefficients' variances, extending the previous work of Ishwaran ...
2. The stochastic fault-tolerant model governed by a stochastic variable in Markov jump model framework, for the first time, is used to cope with the event-triggered dynamic retarded output feedback H∞ control problem for NCSs. It is, therefore, more general than some normal fault-tolerant ...
4.1 Selecting the best Markov-switching dynamic model The study first performs test of model suitability on seven (7) MSDRs (the control variables were included in all). The goal here is to search for the MSDR that best depicts the data patterns shown in Fig. 1. Table 2 shows the vario...