On Sat, 7 Feb 2015, Mike Miller wrote:
res <- residuals( model )
resStd <- ( res - mean( res, na.rm=TRUE ) ) / sd( res, na.rm=TRUE )
Another issue is how to make the theoretical quantiles for the normal
distribution. There are a few methods:
https://www.statsdirect.com/help/data_preparation/normal_scores.htm
I usually use Blom:
r <- rank( resStd )
c <- 3/8
N <- sum( !is.na( resStd ) )
resNorm <- qnorm( ( r - c ) / ( N - 2*c + 1 ) )
resNorm[ is.nan( resNorm ) ] <- NA
Then you could plot it directly:
plot(resNorm, resStd)
When we use qqnorm() in R, it looks like R is using a Blom method with
c=1/2 instead of c=3/8. I believe Blom recommended 3/8 and programs
that offer Blom normal scores use c=3/8.
I don't know if that was off-track because the OP was asking about
density, but he also was asking about checking the distribution of
residuals, so maybe this is appropriate.
I should add, if you don't mind using R's c=1/2, you can get the normal
scores very quickly this way:
resNorm <- qqnorm( residuals( model ), plot.it=FALSE )$x
Apparently, 11 years ago R was using c=3/8 in qqnorm(), so I guess it
changed. Nordheim, Clayton and Yandell wrote about it in this document
dated September 9, 2003:
https://www.stat.wisc.edu/~yandell/st571/R/append8.pdf
It is definitely using c=1/2 today. I don't know where that is
documented.
When I do a QQ-plot of uniform p-values, I like to add a confidence region
with these lmits:
qb95 <- qbeta(.95,1:N,N+1-(1:N))
qb05 <- qbeta(.05,1:N,N+1-(1:N))
If we have N observations from a normal distribution with unknown mean and
variance, can we create some kind of analogous region on a qqnorm() kind
of plot? It seems like there should be a way to get at least an
approximate result using beta and t distributions, probably building on
the qbeta() code above.
Mike
______________________________________________
R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
