The Convex Mixture Distribution: Granger Causality for Categorical Time Series
作者： Alex Tank , Emily B. Fox , Ali Shojaie , Xiudi Li
DOI: 10.1137/20M133097X
关键词: Mixture distribution 、 Categorical variable 、 Distribution (number theory) 、 Granger causality 、 Multivariate statistics 、 Series (mathematics) 、 Regular polygon 、 Mathematics 、 Econometrics
摘要: We present a framework for learning Granger causality networks multivariate categorical time series based on the mixture transition distribution (MTD) model. Traditionally, MTD is plagued by ...
sci-hub.st 参考文章(36)
Martin Jaggi, Revisiting Frank-Wolfe: Projection-Free Sparse Convex Optimization international conference on machine learning. pp. 427- 435 ,(2013)
Daniele P. Radicioni, Roberto Esposito, BREVE: An HMPerceptron-Based Chord Recognition System Advances in Music Information Retrieval. ,vol. 274, pp. 143- 164 ,(2010) , 10.1007/978-3-642-11674-2_7
Adrian E. Raftery, A model for high-order Markov chains Journal of the royal statistical society series b-methodological. ,vol. 47, pp. 528- 539 ,(1985) , 10.1111/J.2517-6161.1985.TB01383.X
Abhra Sarkar, David B. Dunson, Bayesian Nonparametric Modeling of Higher Order Markov Chains Journal of the American Statistical Association. ,vol. 111, pp. 1791- 1803 ,(2016) , 10.1080/01621459.2015.1115763
João Nicolau, A New Model for Multivariate Markov Chains Scandinavian Journal of Statistics. ,vol. 41, pp. 1124- 1135 ,(2014) , 10.1111/SJOS.12087
Benjamin Kedem, Konstantinos Fokianos, Regression models for time series analysis ,(2002)
Jacob Bien, David S. Matteson, William B. Nicholson, Hierarchical Vector Autoregression arXiv: Methodology. ,(2014)
Fang Han, Huanran Lu, Han Liu, None, A direct estimation of high dimensional stationary vector autoregressions Journal of Machine Learning Research. ,vol. 16, pp. 3115- 3150 ,(2015)
Daniel Paulin, Concentration inequalities for Markov chains by Marton couplings and spectral methods Electronic Journal of Probability. ,vol. 20, pp. 1- 32 ,(2015) , 10.1214/EJP.V20-4039
John Duchi, Shai Shalev-Shwartz, Yoram Singer, Tushar Chandra, Efficient projections onto thel1-ball for learning in high dimensions Proceedings of the 25th international conference on Machine learning - ICML '08. pp. 272- 279 ,(2008) , 10.1145/1390156.1390191