phi.mult.ref.cm {AdvBinomApps} | R Documentation |
Function to scale failures tackled by countermeasures in burn-in studies of differently sized reference products down to the greatest common chip size of the products and to merge the downscaled information.
phi.mult.ref.cm(k, n, A.ref, K, theta, prec = 2, tailcut = 1e-08)
k |
vector of total numbers of failures for each reference product. |
n |
vector of numbers of inspected devices for each reference product. |
A.ref |
vector of chip sizes for each reference product (in mm^2). |
K |
matrix with entries K[j,i] denoting the number of failures of the j-th reference product tackled with the i-th countermeasure. If two or more countermeasures
have the same efficiency, they can be handled as one countermeasure for several failures. If the i-th countermeasure does not apply to the j-th reference product, then set K[j,i]=0. If there is no countermeasure for a failure at all, then it does not need to be considered in |
theta |
vector of (different) effectivenesses of countermeasures. |
prec |
precision for greatest common divisor is 10^- |
tailcut |
probabilities for scaled failures smaller than |
phi.cm |
data frame with possible number of failures |
A.gcd |
greatest common divisor of the sizes of the reference products. |
Daniel Kurz, Horst Lewitschnig
Maintainer: Horst Lewitschnig horst.lewitschnig@infineon.com
D. Kurz, H. Lewitschnig and J. Pilz: Failure Probability Estimation with Differently Sized Reference Products for Semiconductor Burn-in Studies. Applied Stochastic Models in Business and Industry, 31(5): 732-744, 2015. DOI: 10.1002/asmb.2100.
D. Kurz, H. Lewitschnig and J. Pilz: Decision-Theoretical Model for Failures Tackled by Countermeasures. IEEE Transactions on Reliability, 63(2): 583-592, 2014. DOI: 10.1109/TR.2014.2315952.
phi.mult.ref
ci.mult.ref
ci.mult.ref.cm
k<-c(1,2) n<-c(10,10) K<-matrix(c(1,0,1,1),2,2,byrow=TRUE) theta<-c(0.7,0.8) A.ref<-c(1,2) phi.mult.ref.cm(k,n,A.ref,K,theta) k<-c(1,2) n<-c(110000,220000) K<-matrix(c(1,0,0,1),2,2,byrow=TRUE) #no CM for one fail! theta<-c(0.7,0.8) A.ref<-c(2,3) phi.mult.ref.cm(k,n,A.ref,K,theta)