Plots two plots side by side. Firstly it draws a Normal QQ-plot of the
residuals, along with a line which has an intercept at the mean of the
residuals and a slope equal to the standard deviation of the
residuals. If shapiro.wilk = TRUE then, in the top left hand corner of the Q-Q plot, the P-value from the
Shapiro-Wilk test for normality is given. Secondly, it draws a
histogram of the residuals. A normal distribution is fitted and
superimposed over the histogram.
Usage
normcheck(x, ...)
## Default S3 method:
normcheck(x, xlab = NULL, main = xlab, col = NULL, shapiro.wilk = FALSE, ...)
## S3 method for class 'lm'
normcheck(x, xlab = NULL, main = xlab, col = NULL, shapiro.wilk = FALSE, ...)
Arguments
x
the residuals from fitting a linear model.
Alternatively, a fitted lm object.
xlab
a title for the x axis: see title.
main
a title for the x axis: see title.
col
a color for the bars of the histogram.
shapiro.wilk
if TRUE, then in the top left hand corner of the Q-Q plot, the P-value from the
Shapiro-Wilk test for normality is displayed.
...
Optional arguments
See Also
"shapiro.test"
Examples
# An exponential growth curve
e<-rnorm(100,0,0.1)
x<-rnorm(100)
y<-exp(5+3*x+e)
fit<-lm(y~x)
normcheck(fit)
# An exponential growth curve with the correct transformation
fit<-lm(log(y)~x)
normcheck(fit)
# Same example as above except we use normcheck.default
normcheck(residuals(fit))
# Peruvian Indians data
data(peru.df)
normcheck(lm(BP~weight, data=peru.df))
providing 
.