harrington2 {desire}R Documentation

Two-sided Harrington type desirability function


Returns a two sided desirability function of the Harrington type. Density, distribution function, quantile function and random number generation for the distribution of the two-sided Harrington desirability function are computed given a normally distributed variable Y with expected value equal to mean and standard deviation equal to sd.


harrington2(LSL, USL, n)
## S3 method for class 'harrington2'
ddesire(x, f, mean, sd)
## S3 method for class 'harrington2'
pdesire(q, f, mean, sd)
## S3 method for class 'harrington2'
qdesire(p, f, mean, sd)
dharrington2(x, LSL, USL, n, mean, sd)
pharrington2(q, LSL, USL, n, mean, sd)
qharrington2(p, LSL, USL, n, mean, sd)
rharrington2(ns, LSL, USL, n, mean, sd)
eharrington2(LSL, USL, n, mean, sd)
vharrington2(LSL, USL, n, mean, sd)



vector of quantiles.


vector of probabilies.


number of observations.


two-sided Harrington type desirability function.


Lower Specification Limit of Y.


Upper Specification Limit of Y.


Kurtosis parameter of desirability function. Values > 1 result in smoother shapes around the target value T = (LSL+USL)/2. Values < 1 already penalize small target deviations.


vector of means.


vector of standard deviations.


harrington2(LSL, USL, n) is the two-sided desirability function of Harrington type (Harrington (1965)). It aims at the specification of desired values of a variable Y which has to be optimized regarding a target value T. Y is transformed onto a unitless scale to the interval [0,1]. LSL and USL are associated with a desirability of 1/e \approx 0.37. LSL and USL have to be chosen symmetrically around the target value T.

The density and distribution functions of Harrington's two-sided desirability function d given a normally distributed variable Y with E(Y)= mean and sd(Y)=sd can be determined analytically, see Trautmann and Weihs (2006).


harrington2(LSL, USL, n) returns a function object of the two-sided desirability function of the Harrington type (see example below).

ddesire / dharrington2 give the density, pdesire / pharrington2 give the distribution function, qdesire / qharrington2 give the quantile function, and rdesire / rharrington2 generate random deviates. edesire / eharrington2 and vdesire / vharrington2 compute the expected value and the variance of the desirability function for a normally distributed random variable Y with E(Y)=mean and sd(Y)=sd.


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.

H. Trautmann, C. Weihs (2006): On the Distribution of the Desirability Index using Harrington's Desirability Function. Metrika 63(2): 207-213.

See Also

harrington1 for one sided Harrington type desirabilities


##Assigning the function object to h: 
h <- harrington2(3,7,1) 

## Plot of desirability function: 

## Desirability function of a vector: 

## d/p/q/r/e/v examples: 
ddesire(4, h, 0, 1)
dharrington2(4, 3, 7, 1, 0, 1) 

ddesire(4, h, c(0,0.5),c(1,1.5))

pdesire(4, h, 0, 1)
pharrington2(4, 3, 7, 1, 0, 1)

qdesire(0.8, h, 0, 1)
qharrington2(0.8, 3, 7, 1, 0, 1)

rdesire(1e6, h, 0, 1)
rharrington2(1e6, 3, 7, 1, 0, 1)



[Package desire version 1.0.7 Index]