Results 251 to 260 of about 105,613 (301)
A data-driven biology-based network model reproduces C. elegans premotor neural dynamics. [PDF]
Morrison M, Young LS.
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On Multi-Parameter Optimization and Proactive Reliability in 5G and Beyond Cellular Networks. [PDF]
Ijaz A, Raza W, Riaz S, Imran A.
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Dynamic neural network modulation associated with rumination in major depressive disorder: a prospective observational comparative analysis of cognitive behavioral therapy and pharmacotherapy. [PDF]
Katayama N +15 more
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Altered brain dynamics in chronic neck and shoulder pain revealed by hidden Markov model. [PDF]
Qiu Z +7 more
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Dynamic Segmentation using Markov-Switching Model
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Moments of Markov switching models [PDF]
Let \(\{\varepsilon_t\}\) be i.i.d. \(N(0,1)\) random variables and \(S_t\) an unobserved stationary ergodic \(k\)-state Markov homogeneous process. The author deals with three types of Markov switching models, namely (MS I) \(y_t=\mu_{S_t} +\sigma_{S_t}\varepsilon_t\), (MS II) \(y_t=\mu_{S_t} +\varphi_1(y_{t-1}-\mu_{S_{t-1}})+\sigma_{S_t}\varepsilon_t\
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Markov-switching mixed-frequency VAR models
International Journal of Forecasting, 2015Abstract This paper introduces regime switching parameters to the Mixed-Frequency VAR model. We begin by discussing estimation and inference for Markov-switching Mixed-Frequency VAR (MSMF-VAR) models. Next, we assess the finite sample performance of the technique in Monte-Carlo experiments.
Foroni, Claudia +2 more
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Testing Markov switching models
Applied Economics, 2014In this article, we propose a new test for Markov switching models. Unlike the tests in the existing literature (e.g. Hansen, 1992; Garcia, 1998; Cho and White, 2007), we focus on testing the null of two regimes, instead of one single regime, in a switching framework.
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