Titlebook: Markov-Switching Vector Autoregressions; Modelling, Statistic Hans-Martin Krolzig Book 1997 Springer-Verlag Berlin Heidelberg 1997 business

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書目名稱Markov-Switching Vector Autoregressions影響因子(影響力)




書目名稱Markov-Switching Vector Autoregressions影響因子(影響力)學(xué)科排名




書目名稱Markov-Switching Vector Autoregressions網(wǎng)絡(luò)公開度




書目名稱Markov-Switching Vector Autoregressions網(wǎng)絡(luò)公開度學(xué)科排名




書目名稱Markov-Switching Vector Autoregressions被引頻次




書目名稱Markov-Switching Vector Autoregressions被引頻次學(xué)科排名




書目名稱Markov-Switching Vector Autoregressions年度引用




書目名稱Markov-Switching Vector Autoregressions年度引用學(xué)科排名




書目名稱Markov-Switching Vector Autoregressions讀者反饋




書目名稱Markov-Switching Vector Autoregressions讀者反饋學(xué)科排名

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The Markov-Switching Vector Autoregressive Model,e fundamental assumptions constituting this class of models. The discussion of the two components of MS-VAR processes will clarify their on time invariant vector auto-regressive and Markov-chain models. Some basic stochastic properties of MS-VAR processes are presented in .. Finally, MS-VAR models a

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The BLHK Filter,ilities. In the MS-VAR model the state vector .. is given a structural interpretation. Thus an inference on this unobserved variable is of interest for its own sake. However, the filtered and smoothed state probabilities provide not only information about the regime at time ., but also open the way

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Maximum Likelihood Estimation,he maximum likelihood estimation of the parameters . of an MS-VAR model is considered. The aim of this chapter is (i.) to provide the reader with an introduction to the methodological issues of ML estimation of MS-VAR models in general, (ii.) to propose with the EM algorithm an estimation technique

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Model Selection and Model Checking,olved questions arising in empirical investigations with MS-VAR models concern the issue of model specification. In . we discussed the asymptotic distribution of the maximum likelihood estimator of MS-VAR models. In the literature (cf. .. [1993]) it has been . that standard asymptotic theory holds:.

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Comparative Analysis of Parameter Estimation in Particular MS-VAR Models,and its conceptional differences to the EM algorithm have been discussed. In this chapter, we will focus on the technical aspects of estimation of the VAR coefficients under the various types of restrictions..

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Extensions of the Basic MS-VAR Model, system is autonomous, .. no exogenous variables enter into the system, (ii.) the regime-dependent parameters depend only on the actual regime but not on the former history, and (iii.) the hidden Markov chain is homogeneous, .. the transition probabilities are time-invariant. As we have seen in the