Package: sesem 1.0.2

sesem: Spatially Explicit Structural Equation Modeling

Structural equation modeling is a powerful statistical approach for the testing of networks of direct and indirect theoretical causal relationships in complex data sets with inter-correlated dependent and independent variables. Here we implement a simple method for spatially explicit structural equation modeling based on the analysis of variance co-variance matrices calculated across a range of lag distances. This method provides readily interpreted plots of the change in path coefficients across scale.

Authors:Eric Lamb [aut, cre], Kerrie Mengersen [aut], Katherine Stewart [aut], Udayanga Attanayake [aut], Steven Siciliano [aut]

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12 exports 2 stars 0.23 score 15 dependencies 16 scripts 717 downloads

Last updated 8 years agofrom:214aa199e6. Checks:OK: 5 NOTE: 2. Indexed: yes.

Exports:avg.modindicesbin.resultsbin.rsquarecalc.distgam.pathmake.binmake.covarmodelsummaryplotbinplotmodelfitplotpathrunModels

Dependencies:bitopscaToolsgplotsgtoolsKernSmoothlatticelavaanMASSMatrixmgcvmnormtnlmenumDerivpbivnormquadprog