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Calculates a normal qq-plot for a vector of data along with 95 percent simultaneous confidence bands.
qqnorm(y, pch = 20, xlab = "Standard Normal Quantiles", ylab = "Sample Quantiles", make.plot = TRUE, ...)
numeric vector of data.
plot symbol to use.
Character string giving abscissa label.
Character string giving ordinate axis label.
logical, should the plot be created (TRUE) or not (FALSE)?
optional arguments to the plot function.
A data frame object is returned invisibly with components:
the data and standard normal quantiles, resp.
lower and upper 95 percent confidence bands.
Confidence intervals are calculated using +/- k, where
k = 0.895 / (sqrt(n) * (1- 0.01 / sqrt(n) + 0.85/n))
Gives a 95 percent asymptotic band based on the Kolmogorov-Smirnov statistic (Doksum and Sievers, 1976).
Doksum, K. A. and G. L. Sievers, 1976. Plotting with confidence: graphical comparisons of two populations. Biometrika, 63 (3), 421--434.
qnorm, qqplot, shiftplot
qnorm
qqplot
shiftplot
# NOT RUN { z <- rexp(100) qqnorm( z) y <- rnorm( 100) qqnorm( y) obj <- qqnorm(y, make.plot=FALSE) str(obj) data( ftcanmax) qqnorm( ftcanmax[,"Prec"]) # }
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