hnplot {unrepx} | R Documentation |
Half-normal plots (Daniel plots) of effects
Description
The hnplot
function constructs a (half-) normal plot of effects (see Daniel 1959) that is traditionally used to identify active effects in a screening experiment. Reference lines and various other options and extensions are supported.
Usage
hnplot(effects, ref = TRUE, half = TRUE, horiz = TRUE, method = "Zahn",
a = 0.375, col = half, pch = 16, ID = FALSE, alpha, ...)
Arguments
effects |
Numeric vector of effects or contrasts to be explored. |
ref |
Logical value. If |
half |
Logical value. If |
horiz |
Logical value. If |
method |
Character value. When |
a |
The adjustment used in scaling and centering ranks in the interval (0, 1). The |
col |
Scalar or vector of colors; or a logical value. If logical, a value of |
pch |
Plotting character(s) to use. |
alpha |
Numeric value. If specified, a null reference distribution for |
ID |
Logical or numeric value. If logical and |
... |
Additional graphical parameters (see |
Details
Use of half = FALSE
is not recommended because it can be misleading to the user. Inactive effects are those that are close to zero, and a regular normal plot displays deviations from normality rather than deviations from zero.
Author(s)
Russell V. Lenth
References
Daniel, C (1959) Use of Half-Normal Plots in Interpreting Factorial Two-Level Experiments. Technometrics, 1(4), 311-341
Mee, R (2015) Discussion: Better, not Fewer, Plots. Journal of Quality Technology, 47(2), 107-109
See Also
Other ways of assessing active effects include a dot plot with a reference curve (refplot
), a pareto plot of effects (see parplot
), and a tabular style of presenting effects and P
values (see eff.test
). For more information on methods, see PSE
and ref.dist
.
Examples
require("unrepx")
hnplot(pdEff, ID = ME(pdEff))