How to add legend of plot.Design function (method=image)? (if (!.R.) )

Hi,

 

When running

 

z <- plot(fit, age=NA, cholesterol=NA, perim=boundaries, method='image')

Legend(z, fun=plogis, at=qlogis(c(.01,.05,.1,.2,.3,.4,.5)),
zlab='Probability') 

 

 And after pointing the cursor to the plot() screen in R, I obtain the
following message:

 

Using function "locator(2)" to place opposite corners of image.legend

Error in Legend.plot.Design(z, fun = plogis, at = qlogis(c(0.01, 0.05,  : 

        couldn't find function "subplot"

 

*How can I position the legend inside the range? (or solve the following
error message).

 

Regards,

Jan

 

 

 

-----Original Message-----
From: Jan Verbesselt [mailto:Jan.Verbesselt at biw.kuleuven.be] 
Sent: Monday, August 22, 2005 4:59 PM
To: 'r-help at stat.math.ethz.ch'
Subject: How to add legend of plot.Design function ( method=image)?

 

 

Dear Rlist,

 

How can the Legend of the plot.Design() function can be visualized?

 

Following the documentation in R, I did the following (see below), only the
'Legend' function doesn't visualize the legend of the 

plot (method='image') of the lrmfit. I tried to change par( margin setting)
but this didn’t solve it.

 

How can this be solved?

 

Thanks a lot,

Jan

 

 

library(Design)

     n <- 1000    # define sample size

     set.seed(17) # so can reproduce the results

     age            <- rnorm(n, 50, 10)

     blood.pressure <- rnorm(n, 120, 15)

     cholesterol    <- rnorm(n, 200, 25)

     sex            <- factor(sample(c('female','male'), n,TRUE))

     label(age)            <- 'Age'      # label is in Hmisc

     label(cholesterol)    <- 'Total Cholesterol'

     label(blood.pressure) <- 'Systolic Blood Pressure'

     label(sex)            <- 'Sex'

     units(cholesterol)    <- 'mg/dl'   # uses units.default in Hmisc

     units(blood.pressure) <- 'mmHg'

 

     # Specify population model for log odds that Y=1

     L <- .4*(sex=='male') + .045*(age-50) +

       (log(cholesterol - 10)-5.2)*(-2*(sex=='female') + 2*(sex=='male'))

     # Simulate bin

     ary y to have Prob(y=1) = 1/[1+exp(-L)]

     y <- ifelse(runif(n) < plogis(L), 1, 0)

 

     ddist <- datadist(age, blood.pressure, cholesterol, sex)

     options(datadist='ddist')

 

     fit <- lrm(y ~ blood.pressure + sex * (age + rcs(cholesterol,4)),

                    x=TRUE, y=TRUE)

 

    boundaries <- perimeter(age, cholesterol, lowess=TRUE)

    plot(age, cholesterol)   # show bivariate data density

    lines(boundaries)        # and perimeter that will be used for 3-D plot

    z <- plot(fit, age=NA, cholesterol=NA, perim=boundaries, method='image')

                              # draws image() plot

                              # don't show estimates where data are sparse

                              # doesn't make sense here since vars don't
interact

    if(!.R.)Legend(z, fun=plogis, at=qlogis(c(.01,.05,.1,.2,.3,.4,.5)),
zlab='Probability')   # gray scale or color legend for prob.