8. SGP accuracy vs penalization plot {SFSI}

Accuracy vs penalization plot

Description

Accuracy as a function of the penalization plot for an object of the class 'SGP'

Usage

## S3 method for class 'SGP'
plot(..., x.stat = c("nsup","lambda"),
          y.stat = c("accuracy","MSE"),
          label = x.stat, nbreaks.x = 6)

Arguments

...

Other arguments to be passed:

• One or more objects of the class 'SGP'

• Optional arguments for method plot: 'xlab', 'ylab', 'main', 'lwd', 'xlim', 'ylim'

• For multi-trait SGP, optional argument 'trait' to plot results for a specific trait

x.stat

(character) Either 'nsup' (number of non-zero regression coefficients entering in the prediction of a given testing individual) or 'lambda' (penalization parameter in log scale) to plot in the x-axis

y.stat

(character) Either 'accuracy' (correlation between observed and predicted values) or 'MSE' (mean squared error) to plot in the y-axis

label

(character) Similar to x.stat but to show the value in x-axis for which the y-axis is maximum

nbreaks.x

(integer) Number of breaks in the x-axis

Value

Creates a plot of either accuracy or MSE versus either the support set size (average number of predictors with non-zero regression coefficient) or versus lambda.

Examples

  # See examples in
  # help(SGP, package="SFSI")