plotStabilityPaths {monaLisa} | R Documentation |
Plot the stability paths of each variable (predictor), showing the selection probability as a function of the regularization step.
plotStabilityPaths( se, selProbMin = metadata(se)$stabsel.params.cutoff, col = "cadetblue", lwd = 1, lty = 1, ylim = c(0, 1.1), ... )
se |
the |
selProbMin |
A numerical scalar in [0,1]. Predictors with a selection
probability greater than |
col |
color of the selected predictors. |
lwd |
line width (default = 1). |
lty |
line type (default = 1). |
ylim |
limits for y-axis (default = c(0,1.1)). |
... |
additional parameters to pass on to |
TRUE
(invisibly).
## create data set Y <- rnorm(n = 500, mean = 2, sd = 1) X <- matrix(data = NA, nrow = length(Y), ncol = 50) for (i in seq_len(ncol(X))) { X[ ,i] <- runif(n = 500, min = 0, max = 3) } s_cols <- sample(x = seq_len(ncol(X)), size = 10, replace = FALSE) for (i in seq_along(s_cols)) { X[ ,s_cols[i]] <- X[ ,s_cols[i]] + Y } ## reproducible randLassoStabSel() with 1 core set.seed(123) ss <- randLassoStabSel(x = X, y = Y) plotStabilityPaths(ss)