# colormap: This function makes a colormap of correlations in a design... In daewr: Design and Analysis of Experiments with R

## Description

This function makes a colormap of the correlations of a design matrix stored in the data frame design

## Usage

 `1` ```colormap(design, mod) ```

## Arguments

 `design` input - a data frame containing columns of the numeric factor levels `mod` input - a number indicationg the model for the colormap 1 = linear model containing only the terms in the dataframe 2 = linear model plus two factor interactions 3 = linear model plus 2 and 3 factor interactions 4 = linear model plus 2, 3, and 4 factor interactions

John Lawson

## Examples

 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44``` ```# color map of 2^(4-1) design library(FrF2) design <- FrF2(8, 4, randomize = FALSE) colormap(design, mod=3) # Makes color map for saturated 2^(7-4) design in Figure 6.14 p. 197 library(FrF2) design <-FrF2( 8, 7) colormap(design, mod=2) # Makes colormap of an Alternate Screening Design library(daewr) ascr<-Altscreen(7) colormap(ascr, mod=2) # Makes colormap of a Model Robust Design library(daewr) MR16 <- ModelRobust('MR16m7g5', randomize = FALSE) colormap(MR16, mod=2) ## The function is currently defined as function(design,mod) { ##################### Inputs ########################################### # design - a data frame containing columns of the numeric factor levels # mod - the model for the color plot of correlations # 1 = Linear model containing only the terms in the data frame # 2 = Linear model plus two factor interactions # 3 = Linear model plus 2 and 3 factor interactions # 4 = Linear model plus 2, 3 and 4 factor interactions ######################################################################## y<-runif(nrow(design),0,1) if(mod==1) {test <- model.matrix(lm(y~(.),data=design))} if(mod==2) {test <- model.matrix(lm(y~(.)^2,data=design))} if(mod==3) {test <- model.matrix(lm(y~(.)^3,data=design))} if(mod==4) {test <- model.matrix(lm(y~(.)^4,data=design))} names<-colnames(test) names<-gsub(':','',names) names<-gsub('1','',names) colnames(test)<-names cmas<-abs(cor(test[,ncol(test):2])) cmas<-cmas[c((ncol(cmas)):1), ] rgb.palette <- colorRampPalette(c("white", "black"), space = "rgb") levelplot(cmas, main="Map of absolute correlations", xlab="", ylab="", col.regions=rgb.palette(120), cuts=100, at=seq(0,1,0.01),scales=list(x=list(rot=90))) } ```

daewr documentation built on May 29, 2017, 6:11 p.m.