phi.mult.ref {AdvBinomApps}

Downscaling of failures to greatest common chip size

Description

Function to scale the numbers of failures 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.

Usage

phi.mult.ref(k, n, A.ref, prec = 2, tailcut = 1e-08)

Arguments

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).

prec

precision for greatest common divisor is 10^-prec (default: 2).

tailcut

probabilities for scaled failures smaller than tailcut are set to zero for each reference product (default: 1e-08). Too small values for tailcut might cause increased computation times.

Value

phi

data frame with possible numbers of failures k.gcd and probabilities phi(k.gcd). Only failure numbers k.gcd with phi(k.gcd)>0 are printed out.

A.gcd

greatest common divisor of the sizes of the reference products.

Author(s)

Daniel Kurz, Horst Lewitschnig

Maintainer: Horst Lewitschnig [e-mail]

References

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.

See Also

ci.mult.ref phi.mult.ref.cm ci.mult.ref.cm

Examples

k<-c(1,2)
n<-c(10,15)
A.ref<-c(2,3)
phi.mult.ref(k,n,A.ref)

k<-c(1,1)
n<-c(110000,220000)
A.ref<-c(5.21,10.71)
phi.mult.ref(k,n,A.ref)

k<-c(1,2,3,4)
n<-c(10,15,20,30)
A.ref<-c(1,2,3,4)
phi.mult.ref(k,n,A.ref)