There is a direct correspondence between the inverse covariance matrix and multiple regression \insertCite kwan2014regression,Stephens1998BGGM. This readily allows for converting the GGM parameters to regression coefficients. All data types are supported.
## S3 method for class 'explore'coef(object, iter =NULL, progress =TRUE,...)
Arguments
object: An Object of class explore.
iter: Number of iterations (posterior samples; defaults to the number in the object).
progress: Logical. Should a progress bar be included (defaults to TRUE) ?
...: Currently ignored.
Returns
An object of class coef, containting two lists.
betas A list of length p, each containing a p - 1 by iter matrix of posterior samples
object An object of class explore (the fitted model).
Examples
# note: iter = 250 for demonstrative purposes# dataY <- ptsd[,1:4]############################# example 1: ordinal ############################## fit model (note + 1, due to zeros)fit <- explore(Y +1, type ="ordinal", iter =250, progress =FALSE, seed =1234)# summarize the partial correlationsreg <- coef(fit, progress =FALSE)# summarysumm <- summary(reg)
summ