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show.ci='FALSE' ignored in simple.lm

3 messages · Elinor Zeev, David Winsemius, Dennis Murphy

David Winsemius
#
On Oct 27, 2011, at 6:58 AM, Elinor Zeev wrote:

            

      
      
      
    

        
My guess (and it is a guess since you did not specify a package for  
simple.lm)  is that specifying a conf.level is over-riding the show.ci  
parameter. Why would one specify a value for "conf.level" if one did  
not want a confidence level?

I have quite few packages loaded and I still get:
 > ?simple.lm
No documentation for 'simple.lm' in specified packages and libraries:
you could try '??simple.lm'

  
    

      
      
    

  


  


      

    

    

      
      

        


  

        

      Dennis Murphy
    

    

      
      #
    

  


  

      
Hi:

A trip to package sos reveals that simple.lm() is in the UsingR
package. Looking at the code of this function, it plots the (x, y)
pairs and the fitted least squares line without an option to suppress
the plot. Here's a slight hack of the function; it adds a new argument
plot with default action TRUE; after the linear model is fit, an if
statement tests to see if the plot is desired; if FALSE, it simply
returns the (print method of the) fitted object.

simple.lm2 <- function (x, y, plot = TRUE, show.residuals = FALSE,
          show.ci = FALSE, conf.level = 0.95, pred = FALSE)
{
    op <- par()
    ord <- order(x)
    x <- x[ord]
    y <- y[ord]
    tmp.lm <- lm(y ~ x)
    if(!plot) return(tmp.lm) else {

    if (show.residuals) {
        par(mfrow = c(2, 2))
    }
    plot(x, y)
    abline(tmp.lm)

    if (show.ci) {
        xvals <- seq(min(x), max(y), length = 15)
        curve(predict(tmp.lm, data.frame(x = x), level = conf.level,
            interval = "confidence")[, 3], add = TRUE)
        curve(predict(tmp.lm, data.frame(x = x), level = conf.level,
            interval = "confidence")[, 2], add = TRUE)
        curve(predict(tmp.lm, data.frame(x = x), level = conf.level,
            interval = "prediction")[, 3], lty = 3, add = TRUE)
        curve(predict(tmp.lm, data.frame(x = x), level = conf.level,
            interval = "prediction")[, 2], lty = 3, add = TRUE)
    }
    coeffs <- floor(tmp.lm$coeff * 100 + 0.5)/100
    plusorminus <- c("+")
    if (coeffs[1] < 0)
        plusorminus <- c("")
    title(paste("y = ", coeffs[2], "x ", plusorminus, coeffs[1]))
    if (show.residuals) {
        Fitted <- fitted.values(tmp.lm)
        Residuals <- residuals(tmp.lm)
        plot(Fitted, Residuals)
        abline(h = 0)
        title("Residuals vs. fitted")
        hist(Residuals, main = "hist of residuals")
        qqnorm(Residuals, main = "normal plot of residuals")
        qqline(Residuals)
    }
    if (pred) {
        print(predict(tmp.lm, data.frame(x = pred)))
    }
      }
    tmp.lm
}


#####
# Simple test:

plot(x <- 1:10)
y <- 5*x + rnorm(10,0,1)

tmp1 <- simple.lm2(x, y, plot = FALSE)
summary(tmp1)
# Produces the plot
simple.lm2(x, y)



HTH,
Dennis

        
On Thu, Oct 27, 2011 at 7:35 AM, David Winsemius <dwinsemius at comcast.net> wrote: