trajC0 | R Documentation |
Plot trajectories.
trajC0(x, ...) ## S3 method for class 'selectboost' trajC0( x, summary.selectboost.res, lasso.coef.path, type.x.axis = "noscale", type.graph = "boost", threshold.level = NULL, ... )
x |
Numerical matrix. Selectboost object. |
... |
. Passed to the plotting functions. |
summary.selectboost.res |
List. Summary of selectboost object. |
lasso.coef.path |
List. Result of |
type.x.axis |
Character value. "scale" or "noscale" for the X axis. |
type.graph |
Character value. Type of graphs: "bars", "lasso" and "boost". |
threshold.level |
Numeric value. Threshold for the graphs. |
trajC0
returns an invisible list and creates four graphics.
An invisible list.
invisible list.
Frederic Bertrand, frederic.bertrand@utt.fr
selectBoost: a general algorithm to enhance the performance of variable selection methods in correlated datasets, Frédéric Bertrand, Ismaïl Aouadi, Nicolas Jung, Raphael Carapito, Laurent Vallat, Seiamak Bahram, Myriam Maumy-Bertrand, Bioinformatics, 2020. doi: 10.1093/bioinformatics/btaa855
fastboost
, autoboost
and summary.selectboost
Other Selectboost analyze functions:
auto.analyze()
,
plot.summary.selectboost()
data(autoboost.res.x) data(diabetes, package="lars") ### With lasso trajectories m.x<-lars::lars(diabetes$x,diabetes$y) plot(m.x) mm.x<-predict(m.x,type="coef",mode="lambda") autoboost.res.x.mean = summary(autoboost.res.x) par(mfrow=c(2,2),mar=c(4,4,1,1)) trajC0(autoboost.res.x,autoboost.res.x.mean,lasso.coef.path=mm.x,type.graph="lasso") trajC0(autoboost.res.x,autoboost.res.x.mean) trajC0(autoboost.res.x,autoboost.res.x.mean,type.graph="bars") trajC0(autoboost.res.x,autoboost.res.x.mean,type.x.axis ="scale")
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