Facilities for constructing variance dispersion graphs, fraction- of-design-space plots and similar graphics for exploring the properties of experimental designs. The design region is explored via random sampling, which allows for more flexibility than traditional variance dispersion graphs. A formula interface is leveraged to provide access to complex model formulae. Graphics can be constructed simultaneously for multiple experimental designs and/or multiple model formulae. Instead of using pointwise optimization to find the minimum and maximum scaled prediction variance curves, which can be inaccurate and time consuming, this package uses quantile regression as an alternative.
|Author||Pieter Schoonees [aut, cre, cph], Niel le Roux [ctb]|
|Date of publication||2016-10-18 10:20:56|
|Maintainer||Pieter Schoonees <email@example.com>|
|License||GPL (>= 2)|
GJ54: Design from Goos & Jones
LHS: Latin Hypercube Sampling
meanspv: Compute Mean Spherical SPV
plot.spv: Plot VDGs or FDS plots
print.spv: Print Method for S3 'spv' classes
runif_sphere: Sampling for hyperspheres/hypercubes
sampler: Sampler Function
spv: Calculate the Scaled Prediction Variance (or SPV)
stdrange: Standardize or Unstandarize the Column Range
vdg-package: Variance Dispersion Graphs, Fraction-of-Design-Space Plots...