{ "_id": "6ae63b2f9ceaa78f200989dc", "Package": "sysbreak", "Title": "Structural Breaks in a System of Equations", "Version": "1.1.0", "Authors@R": "c(\nperson(\"Zhongjun\", \"Qu\", , \"qu@bu.edu\", role = c(\"aut\", \"cre\")),\nperson(\"Cheolju\", \"Kim\", , \"cheolju@bu.edu\", role = \"aut\"),\nperson(\"Pierre\", \"Perron\", role = \"aut\")\n)", "Maintainer": "Zhongjun Qu ", "Description": "Methods for detecting, estimating, and conducting\ninference on multiple structural breaks in a linear system of\nequations, such as multivariate linear regressions, seemingly\nunrelated regressions, vector autoregressions, and network\nvector autoregressions. Breaks can occur in the regression\ncoefficients, the covariance matrix of the errors, or both, and\ncan be restricted to a subset of the coefficients. The main\nfunction, sysbreak(), returns the number of breaks detected and\nconfidence intervals for the break dates and for the regression\ncoefficients. A separate function ordbreak() estimates ordered\nbreaks, in which a break in one subset of equations occurs\nbefore a break in another. Specialized functions for vector\nautoregressions varbreak() and network vector autoregressions\nnetbreak() are also provided. Reference: Qu, Z., and Perron, P.\n(2007). 'Estimating and Testing Structural Changes in\nMultivariate Regressions.' 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