plot.clogitLasso | R Documentation |
clogitLasso
objectPlot the parameter profile associated clogitLasso
object
## S3 method for class 'clogitLasso' plot( x, logLambda = TRUE, add.legend = FALSE, add.labels = TRUE, lty = 1:ncol(x$beta), col = 1:ncol(x$beta), ... )
x |
an objet of type |
logLambda |
Set to TRUE if the horizontal axis is on log scale |
add.legend |
Take the value TRUE if legend should be printed in top right hand corner |
add.labels |
set to TRUE if labels are to be added to curves at leftmost side |
lty |
Same to |
col |
Same to |
... |
additional arguments to plot function |
mixlasso
Avalos, M., Pouyes, H., Grandvalet, Y., Orriols, L., & Lagarde, E. (2015). Sparse conditional logistic regression for analyzing large-scale matched data from epidemiological studies: a simple algorithm. BMC bioinformatics, 16(6), S1. doi: 10.1186/1471-2105-16-S6-S1.
## Not run: # generate data y <- rep(c(1,0), 100) X <- matrix (rnorm(20000, 0, 1), ncol = 100) # pure noise strata <- sort(rep(1:100, 2)) fitLasso <- clogitLasso(X,y,strata,log=TRUE) # plot plot(fitLasso) ## End(Not run)
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