mixexp (version 1.2.7)

EffPlot: This function creates mixture effect plots

Description

This function makes effect plots using the Cox or Piepel directions in constrained mixture space.

Usage

EffPlot(des=NULL,nfac=3,mod=1,dir=1)

Arguments

des

data frame containing the design points and response data for a mixture experiment. The data frame must contain the variables x1, x2 ...xn for the mixture variables, and y for the response. n must be between 2 and 12. Only effect plots for linear models can be made when the number of factors is greater than 6.

nfac

The number of mixture components in the model.

mod

an interger representing the model to be traced: 1 for a linear model, 2 for a quadratic model, and 4 for a special cubic model. For models other than these, use the ModelEff function.

dir

an integer representing the direction for which the effect plot is made: 1 for Piepel direction, 2 for Cox direction.

Value

PX

This is a matrix containing the coordinates of the effect plot traces that are plotted.

References

1. Piepel, G. F. "Measuring Component Effects in Constrained Mixture Experiments" Technometrics, Vol 25, pp. 97-105, 1982.

2. "John Lawson, Cameron Willden (2016).", "Mixture Experiments in R Using mixexp.", "Journal of Statistical Software, Code Snippets, 72(2), 1-20.", "doi:10.18637/jss.v072.c02".

Examples

# NOT RUN {



#Example from Li, Tolley, Lee(2010) response is perm
x1<-c(.572,.358,.286,.286,.286,.143,.357)
x2<-c(.214,.428,.500,.357,.214,.500,.500)
x3<-c(.214,.214,.214,.357,.500,.357,.143)
y<-c(7.7,18.4,24.2,9.8,5.9,23.0,19.4)
des<-data.frame(x1,x2,x3,y)
EffPlot(des,2,2)


#Example from Snee, Marquart(1976)
x1<-c(.1,.1,.1,.15,.1,.1,.1,.4,.35,.30,.1,.45,.45,.45,.45,.45,.259,.259,.259,.259)
x2<-c(.5,.05,.5,.05,.05,.5,.05,.05,.05,.5,.5,.05,.2,.15,.25,.1,.222,.222,.222,.222)
x3<-c(0,0,0,0,.1,.1,.1,.1,.1,0,.1,0,0,0,.1,.1,.05,.05,.05,.05)
x4<-c(0,0,.1,.1,0,.1,.1,.1,.1,0,0,0,.1,.1,0,0,.05,.05,.05,.05)
x5<-c(.1,.55,.1,.6,.55,.1,.55,.1,.1,.1,.2,.45,.1,.1,.1,.1,.244,.244,.244,.244)
x6<-c(.2,.2,.2,.05,.2,.05,.05,.2,.2,.05,.05,.05,.05,.2,.05,.2,.125,.125,.125,.125)
x7<-c(.05,.05,0,.05,0,0,0,.05,.05,0,.05,0,.05,0,.05,0,.025,.025,.025,.025)
x8<-c(.05,.05,0,0,0,.05,.05,0,.05,.05,0,0,.05,0,0,.05,.025,.025,.025,.025)
y<-c(30,113,17,94,89,18,90,20,21,15,28,48,18,7,16,19,38,30,35,40)
des<-data.frame(x1,x2,x3,x4,x5,x6,x7,x8,y)
EffPlot(des,mod=1,dir=1)



# Weed control example from Lawson & Erjavec
x1<-c(1,0,0,.5,.5,0,.33333,.33333,.33333)
x2<-c(0,1,0,.5,0,.5,.33333,.33333,.33333)
x3<-c(0,0,1,0,.5,.5,.33333,.33333,.33333)
y<-c(73,68,80,77,86,75,92,93,88)
des<-data.frame(x1,x2,x3,y)
EffPlot(des,3)



# Polvoron Example from Lawson
des<-Xvert(3,uc=c(.8,.95,.50),lc=c(0,.10,.05),ndm=1,plot=FALSE)
dat<-as.matrix(des)
# remove the edge centroid at the top
dat<-dat[c(1:6,8:11), ]
# add two more centroids
dat<-rbind(dat,dat[10, ],dat[10,])
# response vector
y<-c(5.75,3.69,5.33,5.68,3.85,3.83,5.88,5.87,5.23,6.54,6.82,6.41)
# make the data frame for plotting
des<-data.frame(dat[,1:3],y)
EffPlot(des,3)

# Cornell's example of blending pesticides for control of mites (special cubic model)
mite<-SCD(4)
yavg<-c(1.8,25.4,28.6,38.5,4.9,3.1,28.7,3.4,37.4,10.7,22.0,2.6,2.4,
        11.1,0.8)
mite<-cbind(mite,yavg)
mite2<-mite
names(mite2)<-c("x1","x2","x3","x4","y")
EffPlot(des=mite2,mod=4,dir=2)
# }