plot.glmgraph: Plot coefficients from a "glmgraph" object

In glmgraph: Graph-Constrained Regularization for Sparse Generalized Linear Models

Description

Plot solution path for a fitted "glmgraph" object.

Usage

## S3 method for class 'glmgraph'
plot(x,...)

Arguments

x	Fitted "glmgraph" model.
...	Other graphical parameters to plot

Author(s)

Li Chen <[e-mail]> , Jun Chen <[e-mail]>

References

Li Chen. Han Liu. Hongzhe Li. Jun Chen. (2015) glmgraph: Graph-constrained Regularization for Sparse Generalized Linear Models.(Working paper)

See Also

glmgraph

Examples

 set.seed(1234)
 library(glmgraph)
 n <- 100
 p1 <- 10
 p2 <- 90
 p <- p1+p2
 X <- matrix(rnorm(n*p), n,p)
 magnitude <- 1
 ### construct laplacian matrix from adjacency matrix
 A <- matrix(rep(0,p*p),p,p)
 A[1:p1,1:p1] <- 1
 A[(p1+1):p,(p1+1):p] <- 1
 diag(A) <- 0
 btrue <- c(rep(magnitude,p1),rep(0,p2))
 intercept <- 0
 eta <- intercept+X%*%btrue
 diagL <- apply(A,1,sum)
 L <- -A
 diag(L) <- diagL
 ### gaussian
 Y <- eta+rnorm(n)
 obj <- glmgraph(X,Y,L)
 plot(obj)
 ### binomial
 Y <- rbinom(n,1,prob=1/(1+exp(-eta)))
 obj <- glmgraph(X,Y,L,family="binomial")
 plot(obj) 

glmgraph documentation built on May 1, 2019, 7:04 p.m.