plot.nested.glmnetr {glmnetr}

Plot results from a nested.glmnetr() output

Description

Plot the nested cross validation performance numbers, cross validated relaxed lasso deviances or coefficients from a nested.glmnetr() call.

Usage

## S3 method for class 'nested.glmnetr'
plot(
  x,
  type = "devrat",
  gam = NULL,
  lambda.lo = NULL,
  title = NULL,
  plup = 0,
  coefs = FALSE,
  comment = TRUE,
  pow = 2,
  ylim = 1,
  plot = 1,
  fold = 1,
  xgbsimple = 0,
  ...
)

Arguments

x

A nested.glmnetr output object

type

type of plot to be produced form the (nested) cross validation performance measures, and the lasso model tuning or lasso model coefficients. For the lasso model the options include "lasso" to plot deviances informing hyperparmeter choice or "coef" to plot lasso parameter estimates. Else nested cross validation performance measures are plotted. To show cross validation performance measures the options include "devrat" to plot deviance ratios, i.e. the fractional reduction in deviance relative to the null model deviance, "agree" to plot agreement, "lincal" to plot the linear calibration slope coefficients, "intcal" to plot the linear calibration intercept coefficients or "devian" to plot the deviances from the nested cross validation. For each performance measure estimates from the individual (outer) cross validation fold are depicted by thin lines of different colors and styles, while the composite value from all fol=ds is depicted by a thicker black line, and the performance measures naively calculated on the all data using the model derived from all data is depicted in a thicker red line.

gam

A specific level of gamma for plotting. By default gamma.min will be used. Applies only for type = "lasso".

lambda.lo

A lower limit of lambda when plotting. Applies only for type = "lasso".

title

A title

plup

Plot upper 95 percent two-sided confidence intervals for the deviance plots. Applies only for type = "lasso".

coefs

Depricated. See option 'type'. To plot coefficients specify 'type = coef'.

comment

Default of TRUE to write to console information on lam and gam selected for output. FALSE will suppress this write to console. Applies only for type = "lasso".

pow

Power to which agreement is to be raised when the "gaussian" model is fit, i.e. 2 for R-square, 1 for correlation. Does not apply to type = "lasso".

ylim

y axis limits for model performance plots, i.e. does not apply to type = "lasso". The ridge model may calibrate very poorly obscuring plots for type of "lincal" or "intcal", so one may specify the ylim value. If ylim is set to 1, then the program will derive a reasonable range for ylim. If ylim is set to 0, then the entire range for all models will be displayed. Does not apply to type = "lasso".

plot

By default 1 to produce a plot, 0 to return the data used in the plot in the form of a list.

fold

By default 1 to display model performance estimates form individual folds (or replicaitons for boostrap evaluations) when type of "agree", "intcal", "lincal", "devrat" for "devian". If 0 then the individual fold calculations are not displayed. When there are many replications as sometimes the case when using bootstrap, one may specify the number of randomly selected lines for plotting.

xgbsimple

1 (default) to include results for the untuned XGB model, 0 to not include.

...

Additional arguments passed to the plot function.

Value

This program returns a plot to the graphics window, and may provide some numerical information to the R Console.

Author(s)

Walter Kremers ([e-mail])

See Also

plot_perf_glmnetr , calplot , plot.cv.glmnetr , nested.glmnetr

Examples

sim.data=glmnetr.simdata(nrows=1000, ncols=100, beta=NULL)
xs=sim.data$xs 
y_=sim.data$yt
event=sim.data$event
# for this example we use a small number for folds_n to shorten run time 
fit3 = nested.glmnetr(xs, NULL, y_, event, family="cox", folds_n=3) 
plot(fit3)
plot(fit3, type="coef")