Description Usage Arguments Details Value Author(s) References See Also Examples
Computes the minimum of a number of desirability functions.
1 |
f,... |
desirability functions |
The Desirability Index was introduced by Harrington (1965), and the concept was extended by Derringer and Suich (1980). It is a means for multicriteria (quality) optimization in industrial quality management. All desirability functions of the quality criteria are combined into a univariate global quality criterion in [0,1] which has to be optimized.
The function can be used for Harrington as well as Derringer and Suich desirability functions.
minimumDI(f, ...)
returns a function object of the Minimum
Desirability Index.
Heike Trautmann trautmann@statistik.tu-dortmund.de, Detlef Steuer steuer@hsu-hamburg.de and Olaf Mersmann olafm@statistik.tu-dortmund.de
J. Harrington (1965): The desirability function. Industrial Quality Control, 21: 494-498.
G.C. Derringer, D. Suich (1980): Simultaneous optimization of several response variables. Journal of Quality Technology 12 (4): 214-219.
D. Steuer (2005): Statistische Eigenschaften der Multikriteriellen Optimierung mittels Wuenschbarkeiten. Dissertation, Dortmund University of Technology, http://hdl.handle.net/2003/20171.
H. Trautmann, C. Weihs (2006): On the Distribution of the Desirability Index using Harrington's Desirability Function. Metrika 63(2): 207-213.
harrington1
and harrington2
for Harrington type desirability functions;
derringerSuich
for desirability functions of Derringer and Suich;
geometricDI
,meanDI
for other types of Desirability indices.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 | h1 <- harrington1(-2, .9, 2, .1)
h2 <- harrington2(0, 2, 2)
di <- minimumDI(h1, h2)
di(c(0, 1))
## Desirability Index of vector input:
h <- harrington2(3,7,1)
g <- harrington1(-2, .1, 2, .9)
d <- minimumDI(h, g)
m <- matrix(c(seq(2, 8, 0.1), seq(-2, 4, 0.1)), ncol=2, byrow=FALSE)
apply(m, 1, d)
|
Loading required package: loglognorm
[1] 0.6110686
[1] 0.1000000 0.1186348 0.1389686 0.1608875 0.1842502 0.2088928 0.2346353
[8] 0.2612869 0.2886520 0.3165346 0.3447434 0.3730949 0.4014167 0.4274149
[15] 0.4493290 0.4723666 0.4965853 0.5220458 0.5488116 0.5769498 0.6065307
[22] 0.6338182 0.6556337 0.6764991 0.6964075 0.7153603 0.7333661 0.7504394
[29] 0.7665998 0.7818710 0.7962799 0.8098561 0.8226310 0.8346375 0.8187308
[36] 0.7788008 0.7408182 0.7046881 0.6703200 0.6376282 0.6065307 0.5769498
[43] 0.5488116 0.5220458 0.4965853 0.4723666 0.4493290 0.4274149 0.4065697
[50] 0.3867410 0.3678794 0.3499377 0.3328711 0.3166368 0.3011942 0.2865048
[57] 0.2725318 0.2592403 0.2465970 0.2345703 0.2231302
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