plot_fds function

Fraction of Design Space Plot

Creates a fraction of design space plot

plot_fds(
  genoutput,
  model = NULL,
  continuouslength = 1001,
  plot = TRUE,
  sample_size = 10000,
  yaxis_max = NULL,
  description = "Fraction of Design Space"
)

Arguments

• genoutput: The design, or the output of the power evaluation functions. This can also be a list of several designs, which will result in all of them being plotted in a row (for easy comparison).
• model: Default NULL. The model, if NULL it defaults to the model used in eval_design or gen_design.
• continuouslength: Default 11. The precision of the continuous variables. Decrease for faster (but less precise) plotting.
• plot: Default TRUE. Whether to plot the FDS, or just calculate the cumulative distribution function.
• sample_size: Default 10000. Number of samples to take of the design space.
• yaxis_max: Default NULL. Manually set the maximum value of the prediction variance.
• description: Default Fraction of Design Space. The description to add to the plot. If a vector and multiple designs passed to genoutput, it will be the description for each plot.

Returns

Plots design diagnostics, and invisibly returns the vector of values representing the fraction of design space plot. If multiple designs are passed, this will return a list of all FDS vectors.

Examples

#We can pass either the output of gen_design or eval_design to plot_correlations
#in order to obtain the correlation map. Passing the output of eval_design is useful
#if you want to plot the correlation map from an externally generated design.

#First generate the design:

candidatelist = expand.grid(X1 = c(1, -1), X2 = c(1, -1))

design = gen_design(candidatelist, ~(X1 + X2), 15)

plot_fds(design)