SIRE: Finding Feedback Effects in SEM and Testing for Their Significance

Provides two main functionalities. 1 - Given a system of simultaneous equation, it decomposes the matrix of coefficients weighting the endogenous variables into three submatrices: one includes the subset of coefficients that have a causal nature in the model, two include the subset of coefficients that have a interdependent nature in the model, either at systematic level or induced by the correlation between error terms. 2 - Given a decomposed model, it tests for the significance of the interdependent relationships acting in the system, via Maximum likelihood and Wald test, which can be built starting from the function output. For theoretical reference see Faliva (1992) <doi:10.1007/BF02589085> and Faliva and Zoia (1994) <doi:10.1007/BF02589041>.

Getting started

Package details

AuthorGianmarco Vacca [aut, cre]
MaintainerGianmarco Vacca <[email protected]>
LicenseGPL-3
Version1.1.0
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:
install.packages("SIRE")

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SIRE documentation built on May 1, 2019, 7:30 p.m.