Spatially Explicit Structural Equation Modeling
Function to display averaged modification indices for a spatial SEM
Extract results for a particular bin
Extract r-square values for dependant variables a spatial SEM for a pa...
Calculate intersample distances for a set of X-Y coordinates
Prints and displays spatial sem results using gam models
Function to make lag distance bins
Function to calculate covariance matrices for a set of lag distance bi...
Function to extract and display basic summary information for a spatia...
Function to plot the distribution of lag distance bin sizes
Function to plot model fit indices for spatial SEM analyses
Function to plot spatial SEM results for individual paths
Run a spatial SEM analysis
Spatial structural equation modeling (SESEM)
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.