plot.clogitL1: Plotting after fitting conditional logistic regression with...

In clogitL1: Fitting Exact Conditional Logistic Regression with Lasso and Elastic Net Penalties

Description

Takes a clogitL1 object and plots the parameter profile associated with it.

Usage

 ## S3 method for class 'clogitL1'
 plot(x, logX=T,
	add.legend=F, add.labels=T,
 	lty=1:ncol(x$beta), col=1:ncol(x$beta), ...) 

Arguments

x	an object of type clogitL1.
logX	should the horizontal axis be on log scale?
add.legend	set to TRUE if legend should be printed in top right hand corner. Legend will contain names of variables in data.frame, if specified, otherwise will be numbered from 1 to p in order encountered in original input matrix x
add.labels	set to TRUE if labels are to be added to curves at leftmost side. If variable names are available, these are plotted, otherwise, curves are numbered from 1 to p in order encountered in original input matrix x
lty	usual 'lty' plotting parameter.
col	usual 'col' plotting parameter.
...	additional arguments to plot function

References

http://www.jstatsoft.org/v58/i12/

See Also

clogitL1

Examples

set.seed(145)

# data parameters
K = 10 # number of strata
n = 5 # number in strata
m = 2 # cases per stratum
p = 20 # predictors

# generate data
y = rep(c(rep(1, m), rep(0, n-m)), K)
X = matrix (rnorm(K*n*p, 0, 1), ncol = p) # pure noise
strata = sort(rep(1:K, n))

par(mfrow = c(1,2))
# fit the conditional logistic model
clObj = clogitL1(y=y, x=X, strata)
plot(clObj, logX=TRUE)

# cross validation
clcvObj = cv.clogitL1(clObj)
plot(clcvObj)

Example output

Loading required package: Rcpp

clogitL1 documentation built on May 2, 2019, 3 p.m.