{ "_id": "6a1f182bb401979e7341ec83", "Package": "rsurface", "Type": "Package", "Title": "Design of Rotatable Central Composite Experiments and Response\nSurface Analysis", "Version": "1.1.0", "Authors@R": "c(\nperson(\"Timothy\", \"Schwinghamer\", email =\n\"timothy.schwinghamer@mail.mcgill.ca\", role = c(\"aut\", \"cre\")),\nperson(\"Dutilleul\", \"Pierre\", email =\n\"pierre.dutilleul@mcgill.ca\", role = c(\"aut\", \"cph\")\n)\n)", "Maintainer": "Timothy Schwinghamer ", "Description": "Produces tables with the level of replication (number of\nreplicates) and the experimental uncoded values of the\nquantitative factors to be used for rotatable Central Composite\nDesign (CCD) experimentation and a 2-D contour plot of the\ncorresponding variance of the predicted response according to\nMead et al. (2012) design_ccd(),\nand analyzes CCD data with response surface methodology\nccd_analysis(). A rotatable CCD provides values of the variance\nof the predicted response that are concentrically distributed\naround the average treatment combination used in the\nexperimentation, which with uniform precision (implied by the\nuse of several replicates at the average treatment combination)\nimproves greatly the search and finding of an optimum response.\nThese properties of a rotatable CCD represent undeniable\nadvantages over the classical factorial design, as discussed by\nPanneton et al. (1999) and Mead et\nal. 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