Description Usage Arguments Details Author(s) References See Also Examples
Plots either the estimated features or a heatmap of the
estimated weights from a fitted Fused Lasso Latent Feature (FLLat)
model (i.e., an object of class FLLat
).
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x |
A fitted FLLat model. That is, an object of class
|
type |
The choice of whether to plot the estimated features
\hat{B} or a heatmap of the estimated weights
\hat{Θ}. Default is |
f.mar |
The margins for the plot of each estimated feature. |
f.xlab |
The label for the x-axis for the plot of each estimated feature. |
w.mar |
The margins for the heatmap of the estimated weights. |
samp.names |
The sample names used to label the columns in the heatmap of the estimated weights. |
hc.meth |
The agglomeration method to be used in the hierarchical
clustering of the columns of \hat{Θ}. See |
... |
Further graphical parameters, for the |
This function plots the estimated features \hat{B} or a heatmap of the estimated weights \hat{Θ} from a fitted FLLat model. The features are plotted in order of decreasing total magnitude, where the magnitude is given by sum(\hat{β}_{lj}^2 from l = 1 to L) with \hat{β}_{lj} for l = 1 to L denoting the jth estimated feature (column of \hat{B}). Similarly, the rows of the heatmap of the estimated weights are re-ordered in the same way. The heatmap also includes a dendrogram of a hierarchical clustering of the samples based on their estimated weights (columns of \hat{Θ}).
For more details, please see Nowak and others (2011) and the package vignette.
Gen Nowak gen.nowak@gmail.com, Trevor Hastie, Jonathan R. Pollack, Robert Tibshirani and Nicholas Johnson.
G. Nowak, T. Hastie, J. R. Pollack and R. Tibshirani. A Fused Lasso Latent Feature Model for Analyzing Multi-Sample aCGH Data. Biostatistics, 2011, doi: 10.1093/biostatistics/kxr012
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