BRDT (version 0.1.0)

boptimal_cost: Optimal Test Plans with Minimum Expected Overall Costs in Binomial RDT Design

Description

Define the optimal function to find the optimal test plans with minimum expected overall costs (for binomial RDT).

Usage

boptimal_cost(Cf, Cv, G, Cw, N, Rvec, cvec, pi, thres_CR)

Arguments

Cf

Fixed costs of RDT

Cv

Variable unit costs of RDT

G

Reliabilty growth cost

Cw

Average cost per warranty claim

N

Sales volume

Rvec

Vector of lower level reliability requirements

cvec

Vector of maximum allowable failures

pi

Failure probability

thres_CR

Threshold (acceptable level) of consumer's risk

Value

Vector of optimal test plan parameters, acceptance probabiltiy and cost

See Also

boptimal_n for getting the optial test sample size; bdata_generator for generating optimal test plans dataset;

Examples

# NOT RUN {
Rvec <- seq(0.8, 0.85, 0.01)
cvec <- seq(0, 2, 1)
pi <- pi_MCSim_beta(M = 5000, seed = 10, a = 1, b = 1)
boptimal_cost(Cf = 10, Cv = 10, G = 100, Cw = 10,
N = 100, Rvec = Rvec, cvec = cvec, pi = pi, thres_CR = 0.5);
# }