Fraction of Design Space Plot
Creates a fraction of design space plot
plot_fds( genoutput, model = NULL, continuouslength = 11, plot = TRUE, yaxis_max = NULL, description = "Fraction of Design Space" )
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. |
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. |
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.
#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)
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