Censored Q-Q Plot comparison — cenCompareQQ • NADA2

Produces three quantile-quantile (Q-Q) plots, also called probability plots, based on three distributions (normal, lognormal and gamma distributions).

cenCompareQQ(x.var, cens.var, Yname = yname, printrslt = TRUE, ...)

Arguments

x.var	The column of x (response variable) values plus detection limits
cens.var	The column of indicators, where 1 (or `TRUE`) indicates a detection limit in the `y.var` column, and 0 (or `FALSE`) indicates a detected value in `y.var`.
Yname	Optional – input text in quotes to be used as the variable name on all plots. The default `Yname` is the name of the `y.var` input variable.
printrslt	Logical `TRUE`/`FALSE` option of whether to print the best distribution in the console window, or not. Default is `TRUE.`
...	further graphical parameters (from par), such as srt, family and xpd.

Value

Plots three Q-Q plots based on normal, lognormal and gamma distributions and prints the best-fit distribution.

Details

Produces three Q-Q plots and reports which one has the highest Shapiro-Francia test statistic (W). The distribution with the highest W is the best fit of the three.

References

Helsel, D.R., 2011. Statistics for censored environmental data using Minitab and R, 2nd ed. John Wiley & Sons, USA, N.J.

Millard, S.P., 2013. EnvStats: An R Package for Environmental Statistics. Springer-Verlag, New York.

Shapiro, S.S., Francia, R.S., 1972. An approximate analysis of variance test for normality. Journal of the American Statistical Association 67, 215–216.

Examples


data(Brumbaugh)
cenCompareQQ(Brumbaugh$Hg,Brumbaugh$HgCen)
#> Lognormal is a good fit