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:
sesem_1.0.2.tar.gz
sesem_1.0.2.zip(r-4.5)sesem_1.0.2.zip(r-4.4)sesem_1.0.2.zip(r-4.3)
sesem_1.0.2.tgz(r-4.4-any)sesem_1.0.2.tgz(r-4.3-any)
sesem_1.0.2.tar.gz(r-4.5-noble)sesem_1.0.2.tar.gz(r-4.4-noble)
sesem_1.0.2.tgz(r-4.4-emscripten)sesem_1.0.2.tgz(r-4.3-emscripten)
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')) |
- alexfiord - Alexandra Fiord transect dataset
- plantcomp - Plant Competition dataset
- truelove - Truelove lowland transect dataset
- truelove_covar - Truelove lowland example covariances
- truelove_results - Truelove lowland example sesem output
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 8 years agofrom:214aa199e6. Checks:OK: 5 NOTE: 2. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Nov 23 2024 |
| R-4.5-win | NOTE | Nov 23 2024 |
| R-4.5-linux | NOTE | Nov 23 2024 |
| R-4.4-win | OK | Nov 23 2024 |
| R-4.4-mac | OK | Nov 23 2024 |
| R-4.3-win | OK | Nov 23 2024 |
| R-4.3-mac | OK | Nov 23 2024 |
Exports:avg.modindicesbin.resultsbin.rsquarecalc.distgam.pathmake.binmake.covarmodelsummaryplotbinplotmodelfitplotpathrunModels
Dependencies:bitopscaToolsgplotsgtoolsKernSmoothlatticelavaanMASSMatrixmgcvmnormtnlmenumDerivpbivnormquadprog
