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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sesem.pdf |sesem.html✨
sesem/json (API)
NEWS

# Install 'sesem' in R:
install.packages('sesem', repos = c('https://eric-lamb.r-universe.dev', 'https://cloud.r-project.org'))
Datasets:

On CRAN:

Conda:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

1.58 score 2 stars 19 scripts 441 downloads 12 exports 15 dependencies

Last updated 9 years agofrom:214aa199e6. Checks:6 OK, 3 NOTE. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKMar 23 2025
R-4.5-winNOTEMar 23 2025
R-4.5-macNOTEMar 23 2025
R-4.5-linuxNOTEMar 23 2025
R-4.4-winOKMar 23 2025
R-4.4-macOKMar 23 2025
R-4.4-linuxOKMar 23 2025
R-4.3-winOKMar 23 2025
R-4.3-macOKMar 23 2025

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

Dependencies:bitopscaToolsgplotsgtoolsKernSmoothlatticelavaanMASSMatrixmgcvmnormtnlmenumDerivpbivnormquadprog