In Auburngrads/SMRD: Statistical Methods For Reliability Data
SMRD:::vinny()
library(SMRD)
In this echapter - Planning Accelerated Life Tests
AdhesiveBond example
Get the adheisive bond planning values from simple user-specified information
AdhesiveBond.Weibull.altpv <-
get.alt.plan.values.from.slope.and.point(distribution = "Weibull",
relationship = "Arrhenius",
accelvar.units = c("DegreesC"),
time.units = "Days",
censor.time = 183,
probs = c(.001),
accelvar = c(50),
slope = 0.726,
beta = 1.667)
print(AdhesiveBond.Weibull.altpv)
specify some test plans
AdhesiveBond0.altplan <-
get.alt.test.plan.direct(accel.variable.levels = c(80,100,120),
number.of.units = c(100,100,100),
censor.times = c(243,243,243))
AdhesiveBond1.altplan <-
get.alt.test.plan.direct(accel.variable.levels = c(78,98,120),
number.of.units = c(155,60,84),
censor.times = c(183,183,183))
AdhesiveBond2.altplan <-
get.alt.test.plan.direct(accel.variable.levels = c(80,100,120),
number.of.units = c(212,88,0),
censor.times = c(243,243,243))
AdhesiveBond3.altplan <-
get.alt.test.plan.direct(accel.variable.levels = c(80,100,120),
number.of.units = c(150,60,90),
censor.times = c(243,243,243))
## optimum plan
AdhesiveBond4.altplan <-
get.alt.test.plan.direct(accel.variable.levels = c(95,120),
number.of.units = c(212,88),
censor.times = c(183,183))
print(AdhesiveBond1.altplan)
the following illustrates the frame method of input
AdhesiveBond2.frame <- data.frame(DegreesC = c(80,100,120),
SampleSize = c(150,60,90),
CensorTimes = c(243,243,243))
AdhesiveBond2.altplan <-
get.alt.test.plan.frame(AdhesiveBond2.frame,
levels.columns = "DegreesC",
censor.column = "CensorTimes",
allocation.column = "SampleSize",
describe.string = "AdhesiveBond Test Plan")
print(AdhesiveBond2.altplan)
Make a schematic plot of the model and the test plan
plot(AdhesiveBond1.altplan,
ALT.plan.values = AdhesiveBond.Weibull.altpv,
use.condition = 50)
plot(AdhesiveBond2.altplan,
ALT.plan.values = AdhesiveBond.Weibull.altpv,
use.condition = 50)
plot(AdhesiveBond3.altplan,
ALT.plan.values = AdhesiveBond.Weibull.altpv,
use.condition = 50)
Large-sample evaluation of the test plan
ALT.vcv(AdhesiveBond1.altplan,
ALT.plan.values = AdhesiveBond.Weibull.altpv)
evaluate(AdhesiveBond1.altplan,
ALT.plan.values = AdhesiveBond.Weibull.altpv,
quantile.of.interest = 0.5,
use.condition = 50)
names(AdhesiveBond1.altplan)
names(AdhesiveBond.Weibull.altpv)
Evaluate the test plan with simulation and large-sample approx
simulate(AdhesiveBond1.altplan,
ALT.plan.values = AdhesiveBond.Weibull.altpv,
use.condition = 50)
unfold(AdhesiveBond1.altplan,
AdhesiveBond.Weibull.altpv,
use.condition = 50)
evaluate(AdhesiveBond1.altplan,
AdhesiveBond.Weibull.altpv,
use.condition = 50,
quantile.of.interest = 0.5)
Evaluate the the other test plans
simulate(AdhesiveBond2.altplan,
ALT.plan.values = AdhesiveBond.Weibull.altpv,
use.condition = 50,
show.detail.on = 5)
simulate(AdhesiveBond2.altplan,
ALT.plan.values = AdhesiveBond.Weibull.altpv,
number.sim = 100,
use.condition = 50)
evaluate(AdhesiveBond2.altplan,
AdhesiveBond.Weibull.altpv,
use.condition = 50,
quantile.of.interest = 0.1)
AdhesiveBond3.sim.out <-
simulate(AdhesiveBond3.altplan,
ALT.plan.values = AdhesiveBond.Weibull.altpv,
use.condition = 50)
ALT.plot.time.v.x(AdhesiveBond3.sim.out,
x.of.interest = c(45))
ALT.plot.FracFail.v.Time(AdhesiveBond3.sim.out,
x.of.interest = c(45))
evaluate(AdhesiveBond3.altplan,
AdhesiveBond.Weibull.altpv,
use.condition = 50,
quantile.of.interest = 0.1)
SMRD:::plot.vpm.vs.size(vpm.vec = c(100, 150, 200),
size.vec = c(1, 2, 3))
SMRD:::plot.volt.vs.size(volts.vec = c(100, 200, 300),
size.vec = c(1, 2, 3))
DeviceA example
DeviceA.altpv <-
get.alt.plan.values.from.slope.and.point(distribution = "Lognormal",
slope = 0.63,
relationship = "Arrhenius",
time.units = "Hours",
censor.time = 5000,
probs = 0.5469,
accelvar = 60,
sigma = 0.98,
use.conditions = 10)
print(DeviceA.altpv)
DeviceA1.altplan <-
get.alt.test.plan.direct(accel.variable.levels = c(10,40,60,80),
number.of.units = c(30,100,20,15),
censor.time = c(5000,5000,5000,5000))
print(DeviceA1.altplan)
simulate(DeviceA1.altplan,
ALT.plan.values = DeviceA.altpv,
nsim = 100,
use.condition = 10)
DeviceA2.altplan <-
get.alt.test.plan.direct(accel.variable.levels = c(10,40,50,60,70,80),
number.of.units = c(30,27,27,27,27,27),
censor.time = c(5000,5000,5000,5000,5000,5000))
print(DeviceA2.altplan)
simulate(DeviceA2.altplan,
ALT.plan.values = DeviceA.altpv,
nsim = 100,
use.condition = 10)
Can't find this function
## generate ALT plans
hold.altplan("Weibull",
a = -4,
b1 = -10,
perc = 0.1,
iopta = 3,
iopts = 2,
pifix = 0)
print(AdhesiveBond.Weibull.altpv)
evaluate(altplan(AdhesiveBond.Weibull.altpv,
"Optimum",
use.condition = 50,
highest.condition = 120,
censor.time = 183,
quantile = 0.1,
sample.size = 300),
AdhesiveBond.Weibull.altpv,
use.condition = 50,
quantile.of.interest = 0.1)
AdhesiveBond.Weibull.optc.altplan <-
altplan(AdhesiveBond.Weibull.altpv,
"Optimized compromise",
use.condition = 50,
highest.condition = 120,
censor.time = 250,
quantile = 0.1)
evaluate(altplan(AdhesiveBond.Weibull.altpv,
"Equal expected",
use.condition = 50,
highest.condition = 120,
censor.time = 250,
quantile = 0.1),
AdhesiveBond.Weibull.altpv,
use.condition = 50,
quantile.of.interest = 0.1)
AdhesiveBond.Weibull.421.altplan <-
altplan(AdhesiveBond.Weibull.altpv,
"421",
use.condition = 50,
highest.condition = 120,
censor.time = 250,
quantile = 0.1)
evaluate(altplan(AdhesiveBond.Weibull.altpv,
"Traditional",
use.condition = 50,
highest.condition = 120,
censor.time = 250,
quantile = 0.1),
AdhesiveBond.Weibull.altpv,
use.condition = 50,
quantile.of.interest = 0.1)
print(AdhesiveBond.Weibull.421.altplan)
evaluate(AdhesiveBond.Weibull.421.altplan,
AdhesiveBond.Weibull.altpv,
use.condition = 50,
quantile.of.interest = 0.1)
unfold(AdhesiveBond.Weibull.421.altplan,
AdhesiveBond.Weibull.altpv,
use.condition = 50)
plot(AdhesiveBond.Weibull.421.altplan,
AdhesiveBond.Weibull.altpv,
use.condition = 50)
DeviceA.Sim.out <-
simulate(DeviceA2.altplan,
ALT.plan.values = DeviceA.altpv,
nsim = 10,
use.condition = 10)
DeviceA.Sim.out500 <-
simulate(DeviceA2.altplan,
ALT.plan.values = DeviceA.altpv,
nsim = 500,
use.condition = 10)
marginalize.sim(DeviceA.Sim.out,
focus.quantity = "parameter",
focus.quantity.detail = 1,
x.of.interest = 50)
marginalize.sim(DeviceA.Sim.out,
focus.quantity = "parameter",
focus.quantity.detail = 2,
x.of.interest = 50)
marginalize.sim(DeviceA.Sim.out,
focus.quantity ="parameter",
focus.quantity.detail = 3,
x.of.interest = 50)
marginalize.sim(DeviceA.Sim.out,
focus.quantity = "parameter",
focus.quantity.detail = "sigma",
x.of.interest = 50)
marginalize.sim(DeviceA.Sim.out,
focus.quantity = "quantile",
focus.quantity.detail = 0.1,
x.of.interest = 50)
marginalize.sim(DeviceA.Sim.out,
focus.quantity = "failure probability",
focus.quantity.detail = 4268.884,
x.of.interest = 50)
SMRD:::plot.marginals.sim(DeviceA.Sim.out,
focus.quantity = "parameter",
focus.quantity.detail = 1)
SMRD:::plot.marginals.sim(DeviceA.Sim.out,
focus.quantity = "parameter",
focus.quantity.detail = 1,
plot.type = "density")
SMRD:::plot.joint.sim(DeviceA.Sim.out,
focus.quantity1 = "quantile",
focus.quantity.detail1 = 0.1,
x.of.interest1 = 50,
focus.quantity2 = "parameter",
focus.quantity.detail2 = 3,
x.of.interest2 = NA)
SMRD:::plot.joint.and.marginals.sim(DeviceA.Sim.out,
focus.quantity1 = "quantile",
focus.quantity.detail1 = 0.1,
x.of.interest1 = 50,
focus.quantity2 = "parameter",
focus.quantity.detail2 = 3,
x.of.interest2 = NA)
summarize.simultation.results(DeviceA.Sim.out,
"Marginal only",
focus.quantity1 = "quantile",
focus.quantity.detail1 = 0.1,
x.of.interest1 = 50,
focus.quantity2 = "parameter",
focus.quantity.detail2 = 3,
x.of.interest2 = NA)
summarize.simultation.results(DeviceA.Sim.out,
"Marginal only",
focus.quantity1 = "quantile",
focus.quantity.detail1 = 0.1,
x.of.interest1 = 50,
focus.quantity2 = "parameter",
focus.quantity.detail2 = 3,
x.of.interest2 = NA,
plot.type = "density")
summarize.simultation.results(DeviceA.Sim.out,
"Joint and Marginal",
focus.quantity1 = "quantile",
focus.quantity.detail1 = 0.1,
x.of.interest1 = 50,
focus.quantity2 = "parameter",
focus.quantity.detail2 = 3,
x.of.interest2 = NA,
plot.type="density")
summarize.simultation.results(DeviceA.Sim.out,
"Joint only",
focus.quantity1 = "quantile",
focus.quantity.detail1 = 0.1,
x.of.interest1 = 50,
focus.quantity2 = "parameter",
focus.quantity.detail2 = 3,
x.of.interest2=NA)
two variable alt planning examples
These methods also apply for tests with more than two variables)
## DeviceR example define two-variable planning values
DeviceR.Weibull.altpv <-
get.alt.plan.values.from.slope.and.point(distribution = "Weibull",
slope = c(.6265,-.4),
relationship = c("Arrhenius","Humidity"),
time.units = "Days",
censor.time = 183,
probs = c(.002),
accelvar = c(50,30),
beta = 1.667,
use.conditions = c(50,30))
print(DeviceR.Weibull.altpv)
Define two-variable ALT test plans
DeviceR.altplan <-
get.alt.test.plan.direct(accel.variable.levels = cbind(c(80,80,120,120),
c(50,80,50,80)),
number.of.units = c(10,10,10,10),
censor.times = c(365,365,365,365),
accelvar.names = c("DegreesC","RH"),
describe.string = "DeviceR Simple Plan")
print(DeviceR.altplan)
Compute the fisher and vcv matrices
ALT.vcv(DeviceR.altplan,DeviceR.Weibull.altpv)
compute the large-sample approximate precision (R) factors
evaluate(DeviceR.altplan, DeviceR.Weibull.altpv,quantile.of.interest=c(.1,.5))
sample size needed for a given value of R
plot(DeviceR.altplan,
DeviceR.Weibull.altpv)
SMRD:::plot.alt.sample.size(DeviceR.altplan,
DeviceR.Weibull.altpv)
## simulate the ALT plans with option to see detail on some experiments
DeviceR.sim.out <- ALTsim(DeviceR.altplan,
DeviceR.Weibull.altpv,
number.sim = 400,
show.detail.on = 5)
DeviceR.sim.out <- ALTsim(DeviceR.altplan,
DeviceR.Weibull.altpv,
number.sim = 400,
show.detail.on = 0)
## simulate the ALT plans and plot summary
DeviceR.sim.out <-
simulate(DeviceR.altplan,
ALT.plan.values = DeviceR.Weibull.altpv,
nsim = 400,
show.detail.on = 5)
DeviceR.sim.out <-
simulate(DeviceR.altplan,
ALT.plan.values = DeviceR.Weibull.altpv,
nsim = 400,
show.detail.on = 0)
## plot the ALT simulation results
ALT.plot.time.v.x(DeviceR.sim.out)
ALT.plot.time.v.x(DeviceR.sim.out,
focus.variable = 2)
ALT.plot.time.v.x(DeviceR.sim.out,
x.of.interest = c(25,10),
xlim = c(20,80))
ALT.plot.FracFail.v.Time(DeviceR.sim.out)
ALT.plot.FracFail.v.Time(DeviceR.sim.out,
x.of.interest = c(25,10),
xlim = c(100,10000))
## look at joint and marginal disributions of focus quantities
summarize.simultation.results(DeviceR.sim.out,
"Joint and Marginal",
focus.quantity1 = "quantile",
focus.quantity.detail1 = 0.1,
x.of.interest1 = "60;20",
focus.quantity2 = "parameter",
focus.quantity.detail2 = 3,
x.of.interest2 = NA,
plot.type = "density")
summarize.simultation.results(DeviceR.sim.out,
"Marginal only",
focus.quantity1 = "quantile",
focus.quantity.detail1 = 0.1,
x.of.interest1 = "60;20",
focus.quantity2 = "parameter",
focus.quantity.detail2 = 3,
x.of.interest2 = NA)
summarize.simultation.results(DeviceR.sim.out,
"Marginal only",
focus.quantity1 = "quantile",
focus.quantity.detail1 = 0.1,
x.of.interest1 = "60;20",
focus.quantity2 = "parameter",
focus.quantity.detail2 = 1,
x.of.interest2 = NA,
plot.type = "density")
summarize.simultation.results(DeviceR.sim.out,
"Joint and Marginal",
focus.quantity1 = "quantile",
focus.quantity.detail1 = 0.1,
x.of.interest1 = "60;20",
focus.quantity2 = "parameter",
focus.quantity.detail2 = 2,
x.of.interest2 = NA,
plot.type = "density")
summarize.simultation.results(DeviceR.sim.out,
"Joint only",
focus.quantity1 = "quantile",
focus.quantity.detail1 = 0.1,
x.of.interest1 = "60;20",
focus.quantity2 = "parameter",
focus.quantity.detail2 = 4,
x.of.interest2 = NA)
NelsonInsulation example from page 350 of Nelson (1990) and Escobar and Meeker (1995) and Meeker and Escobar (1998) page 548
define two-variable planning values
NelsonInsulation.Weibull.altpv <-
get.alt.plan.values.from.slope.and.point(distribution = "Weibull",
slope= c(-12.28,-1.296),
relationship = c("log","log"),
accelvar.units = c("vpm","cm"),
time.units = "Hours",
censor.time = 1000,
probs = c(1.8e-6),
accelvar = c(80,.266),
beta = 1/.6734,
use.conditions = c(80,.266))
print(NelsonInsulation.Weibull.altpv)
## define two-variable ALT test plans
levels = cbind(c(120,120,120,150,150,150,175,175,175,200,200,200),
c(.163,.266,.355,.163,.266,.355,.163,.266,.355,.163,.266,.355))
units = c(11,18,11,8,14,8,8,14,8,11,18,11)
NelsonInsulation.altplan <-
get.alt.test.plan.direct(accel.variable.levels = levels,
number.of.units = units,
censor.times = rep(1000,12),
accelvar.names = c("Volts per mm","Thick"),
describe.string = "NelsonInsulation Factorial Plan")
print(NelsonInsulation.altplan)
print(NelsonInsulation.Weibull.altpv)
## compute the fisher and vcv matrices
ALT.vcv(NelsonInsulation.altplan,
NelsonInsulation.Weibull.altpv)
## compute the large-sample approximate precision (R) factors
evaluate(NelsonInsulation.altplan,
NelsonInsulation.Weibull.altpv,
quantile.of.interest = c(.1,.5))
evaluate(NelsonInsulation.altplan,
NelsonInsulation.Weibull.altpv,
use.conditions = c(175,.163),
quantile.of.interest = c(.1,.5))
evaluate(NelsonInsulation.altplan,
NelsonInsulation.Weibull.altpv,
use.conditions = c(100,.1),
quantile.of.interest = c(.1,.5))
## sample size needed for a given value of R
SMRD:::plot.alt.sample.size(NelsonInsulation.altplan,
NelsonInsulation.Weibull.altpv)
NelsonInsulation.sim.out <- ALTsim(NelsonInsulation.altplan,
NelsonInsulation.Weibull.altpv,
number.sim = 400,
show.detail.on = 1)
ALT.plot.time.v.x(NelsonInsulation.sim.out)
ALT.plot.time.v.x(NelsonInsulation.sim.out,
x.of.interest = c(100,.1),
xlim = c(100,200))
ALT.plot.FracFail.v.Time(NelsonInsulation.sim.out)
ALT.plot.FracFail.v.Time(NelsonInsulation.sim.out,
x.of.interest = c(25,10),
xlim = c(100,10000))
summarize.simultation.results(NelsonInsulation.sim.out,
"Joint and Marginal",
focus.quantity1 = "quantile",
focus.quantity.detail1 = 0.1,
x.of.interest1 = "100;.1",
focus.quantity2 = "parameter",
focus.quantity.detail2 = 3,
x.of.interest2 = NA,
plot.type = "density")
## examples using basic simulation routine
test.matrix <- cbind(V1 = c(1,1,2,2),V2 = c(1,2,1,2))
altsim.out <- altsim(accel.var.mat = test.matrix,
nsamsz = c(4,4,4,4),
centim = c(40000,40000,40000,40000),
theta = c(1,-24,5,1),
distribution = "normal",
number.sim = 10,
debug = F)
altsim.out <- altsim(accel.var.mat = as.matrix(c(1,2,3,4)),
nsamsz = c(4,4,4,4),
centim = c(200,200,200,200),
theta = c(1,-2,3),
distribution = "normal",
number.sim = 5,
debug = F,
kprint = 0)
altsimReturnFrame(accel.var.mat = test.matrix,
nsamsz = c(4,4,4,4),
centim = c(100,100,100,100),
theta = c(1,1,1,2),
distribution =" lognormal",
relationship = c("linear","log"))
## Simulate a single ALT data set
altsimReturnFrame(accel.var.mat = test.matrix,
nsamsz = c(4,4,4,4),
centim = c(100,100,100,100),
theta = c(1,1,1,2),
distribution = "lognormal",
relationship = c("linear","log"))
## example of multiple minima
varone.grid(a = -0.9,
b1 = -7.9,
perc = 0.01,
xlab = "xiL",
ylab = "piL",
xiL.lower = -1,
levels = c(.001,.01,0.10000000000000001, 0.20000000000000001, 0.5, 1, 2),
dump = T)
Auburngrads/SMRD documentation built on Sept. 14, 2020, 2:21 a.m.
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SMRD:::vinny() library(SMRD)
In this echapter - Planning Accelerated Life Tests
AdhesiveBond example
Get the adheisive bond planning values from simple user-specified information
AdhesiveBond.Weibull.altpv <- get.alt.plan.values.from.slope.and.point(distribution = "Weibull", relationship = "Arrhenius", accelvar.units = c("DegreesC"), time.units = "Days", censor.time = 183, probs = c(.001), accelvar = c(50), slope = 0.726, beta = 1.667) print(AdhesiveBond.Weibull.altpv)
specify some test plans
AdhesiveBond0.altplan <- get.alt.test.plan.direct(accel.variable.levels = c(80,100,120), number.of.units = c(100,100,100), censor.times = c(243,243,243)) AdhesiveBond1.altplan <- get.alt.test.plan.direct(accel.variable.levels = c(78,98,120), number.of.units = c(155,60,84), censor.times = c(183,183,183)) AdhesiveBond2.altplan <- get.alt.test.plan.direct(accel.variable.levels = c(80,100,120), number.of.units = c(212,88,0), censor.times = c(243,243,243)) AdhesiveBond3.altplan <- get.alt.test.plan.direct(accel.variable.levels = c(80,100,120), number.of.units = c(150,60,90), censor.times = c(243,243,243)) ## optimum plan AdhesiveBond4.altplan <- get.alt.test.plan.direct(accel.variable.levels = c(95,120), number.of.units = c(212,88), censor.times = c(183,183)) print(AdhesiveBond1.altplan)
the following illustrates the frame method of input
AdhesiveBond2.frame <- data.frame(DegreesC = c(80,100,120), SampleSize = c(150,60,90), CensorTimes = c(243,243,243)) AdhesiveBond2.altplan <- get.alt.test.plan.frame(AdhesiveBond2.frame, levels.columns = "DegreesC", censor.column = "CensorTimes", allocation.column = "SampleSize", describe.string = "AdhesiveBond Test Plan") print(AdhesiveBond2.altplan)
Make a schematic plot of the model and the test plan
plot(AdhesiveBond1.altplan, ALT.plan.values = AdhesiveBond.Weibull.altpv, use.condition = 50) plot(AdhesiveBond2.altplan, ALT.plan.values = AdhesiveBond.Weibull.altpv, use.condition = 50) plot(AdhesiveBond3.altplan, ALT.plan.values = AdhesiveBond.Weibull.altpv, use.condition = 50)
Large-sample evaluation of the test plan
ALT.vcv(AdhesiveBond1.altplan, ALT.plan.values = AdhesiveBond.Weibull.altpv) evaluate(AdhesiveBond1.altplan, ALT.plan.values = AdhesiveBond.Weibull.altpv, quantile.of.interest = 0.5, use.condition = 50) names(AdhesiveBond1.altplan) names(AdhesiveBond.Weibull.altpv)
Evaluate the test plan with simulation and large-sample approx
simulate(AdhesiveBond1.altplan, ALT.plan.values = AdhesiveBond.Weibull.altpv, use.condition = 50) unfold(AdhesiveBond1.altplan, AdhesiveBond.Weibull.altpv, use.condition = 50) evaluate(AdhesiveBond1.altplan, AdhesiveBond.Weibull.altpv, use.condition = 50, quantile.of.interest = 0.5)
Evaluate the the other test plans
simulate(AdhesiveBond2.altplan, ALT.plan.values = AdhesiveBond.Weibull.altpv, use.condition = 50, show.detail.on = 5) simulate(AdhesiveBond2.altplan, ALT.plan.values = AdhesiveBond.Weibull.altpv, number.sim = 100, use.condition = 50) evaluate(AdhesiveBond2.altplan, AdhesiveBond.Weibull.altpv, use.condition = 50, quantile.of.interest = 0.1) AdhesiveBond3.sim.out <- simulate(AdhesiveBond3.altplan, ALT.plan.values = AdhesiveBond.Weibull.altpv, use.condition = 50) ALT.plot.time.v.x(AdhesiveBond3.sim.out, x.of.interest = c(45)) ALT.plot.FracFail.v.Time(AdhesiveBond3.sim.out, x.of.interest = c(45)) evaluate(AdhesiveBond3.altplan, AdhesiveBond.Weibull.altpv, use.condition = 50, quantile.of.interest = 0.1) SMRD:::plot.vpm.vs.size(vpm.vec = c(100, 150, 200), size.vec = c(1, 2, 3)) SMRD:::plot.volt.vs.size(volts.vec = c(100, 200, 300), size.vec = c(1, 2, 3))
DeviceA example
DeviceA.altpv <- get.alt.plan.values.from.slope.and.point(distribution = "Lognormal", slope = 0.63, relationship = "Arrhenius", time.units = "Hours", censor.time = 5000, probs = 0.5469, accelvar = 60, sigma = 0.98, use.conditions = 10) print(DeviceA.altpv) DeviceA1.altplan <- get.alt.test.plan.direct(accel.variable.levels = c(10,40,60,80), number.of.units = c(30,100,20,15), censor.time = c(5000,5000,5000,5000)) print(DeviceA1.altplan) simulate(DeviceA1.altplan, ALT.plan.values = DeviceA.altpv, nsim = 100, use.condition = 10) DeviceA2.altplan <- get.alt.test.plan.direct(accel.variable.levels = c(10,40,50,60,70,80), number.of.units = c(30,27,27,27,27,27), censor.time = c(5000,5000,5000,5000,5000,5000)) print(DeviceA2.altplan) simulate(DeviceA2.altplan, ALT.plan.values = DeviceA.altpv, nsim = 100, use.condition = 10)
Can't find this function
## generate ALT plans hold.altplan("Weibull", a = -4, b1 = -10, perc = 0.1, iopta = 3, iopts = 2, pifix = 0)
print(AdhesiveBond.Weibull.altpv) evaluate(altplan(AdhesiveBond.Weibull.altpv, "Optimum", use.condition = 50, highest.condition = 120, censor.time = 183, quantile = 0.1, sample.size = 300), AdhesiveBond.Weibull.altpv, use.condition = 50, quantile.of.interest = 0.1) AdhesiveBond.Weibull.optc.altplan <- altplan(AdhesiveBond.Weibull.altpv, "Optimized compromise", use.condition = 50, highest.condition = 120, censor.time = 250, quantile = 0.1) evaluate(altplan(AdhesiveBond.Weibull.altpv, "Equal expected", use.condition = 50, highest.condition = 120, censor.time = 250, quantile = 0.1), AdhesiveBond.Weibull.altpv, use.condition = 50, quantile.of.interest = 0.1) AdhesiveBond.Weibull.421.altplan <- altplan(AdhesiveBond.Weibull.altpv, "421", use.condition = 50, highest.condition = 120, censor.time = 250, quantile = 0.1) evaluate(altplan(AdhesiveBond.Weibull.altpv, "Traditional", use.condition = 50, highest.condition = 120, censor.time = 250, quantile = 0.1), AdhesiveBond.Weibull.altpv, use.condition = 50, quantile.of.interest = 0.1) print(AdhesiveBond.Weibull.421.altplan) evaluate(AdhesiveBond.Weibull.421.altplan, AdhesiveBond.Weibull.altpv, use.condition = 50, quantile.of.interest = 0.1) unfold(AdhesiveBond.Weibull.421.altplan, AdhesiveBond.Weibull.altpv, use.condition = 50) plot(AdhesiveBond.Weibull.421.altplan, AdhesiveBond.Weibull.altpv, use.condition = 50) DeviceA.Sim.out <- simulate(DeviceA2.altplan, ALT.plan.values = DeviceA.altpv, nsim = 10, use.condition = 10) DeviceA.Sim.out500 <- simulate(DeviceA2.altplan, ALT.plan.values = DeviceA.altpv, nsim = 500, use.condition = 10) marginalize.sim(DeviceA.Sim.out, focus.quantity = "parameter", focus.quantity.detail = 1, x.of.interest = 50) marginalize.sim(DeviceA.Sim.out, focus.quantity = "parameter", focus.quantity.detail = 2, x.of.interest = 50) marginalize.sim(DeviceA.Sim.out, focus.quantity ="parameter", focus.quantity.detail = 3, x.of.interest = 50) marginalize.sim(DeviceA.Sim.out, focus.quantity = "parameter", focus.quantity.detail = "sigma", x.of.interest = 50) marginalize.sim(DeviceA.Sim.out, focus.quantity = "quantile", focus.quantity.detail = 0.1, x.of.interest = 50) marginalize.sim(DeviceA.Sim.out, focus.quantity = "failure probability", focus.quantity.detail = 4268.884, x.of.interest = 50) SMRD:::plot.marginals.sim(DeviceA.Sim.out, focus.quantity = "parameter", focus.quantity.detail = 1) SMRD:::plot.marginals.sim(DeviceA.Sim.out, focus.quantity = "parameter", focus.quantity.detail = 1, plot.type = "density") SMRD:::plot.joint.sim(DeviceA.Sim.out, focus.quantity1 = "quantile", focus.quantity.detail1 = 0.1, x.of.interest1 = 50, focus.quantity2 = "parameter", focus.quantity.detail2 = 3, x.of.interest2 = NA) SMRD:::plot.joint.and.marginals.sim(DeviceA.Sim.out, focus.quantity1 = "quantile", focus.quantity.detail1 = 0.1, x.of.interest1 = 50, focus.quantity2 = "parameter", focus.quantity.detail2 = 3, x.of.interest2 = NA) summarize.simultation.results(DeviceA.Sim.out, "Marginal only", focus.quantity1 = "quantile", focus.quantity.detail1 = 0.1, x.of.interest1 = 50, focus.quantity2 = "parameter", focus.quantity.detail2 = 3, x.of.interest2 = NA) summarize.simultation.results(DeviceA.Sim.out, "Marginal only", focus.quantity1 = "quantile", focus.quantity.detail1 = 0.1, x.of.interest1 = 50, focus.quantity2 = "parameter", focus.quantity.detail2 = 3, x.of.interest2 = NA, plot.type = "density") summarize.simultation.results(DeviceA.Sim.out, "Joint and Marginal", focus.quantity1 = "quantile", focus.quantity.detail1 = 0.1, x.of.interest1 = 50, focus.quantity2 = "parameter", focus.quantity.detail2 = 3, x.of.interest2 = NA, plot.type="density") summarize.simultation.results(DeviceA.Sim.out, "Joint only", focus.quantity1 = "quantile", focus.quantity.detail1 = 0.1, x.of.interest1 = 50, focus.quantity2 = "parameter", focus.quantity.detail2 = 3, x.of.interest2=NA)
two variable alt planning examples
These methods also apply for tests with more than two variables)
## DeviceR example define two-variable planning values DeviceR.Weibull.altpv <- get.alt.plan.values.from.slope.and.point(distribution = "Weibull", slope = c(.6265,-.4), relationship = c("Arrhenius","Humidity"), time.units = "Days", censor.time = 183, probs = c(.002), accelvar = c(50,30), beta = 1.667, use.conditions = c(50,30)) print(DeviceR.Weibull.altpv)
Define two-variable ALT test plans
DeviceR.altplan <- get.alt.test.plan.direct(accel.variable.levels = cbind(c(80,80,120,120), c(50,80,50,80)), number.of.units = c(10,10,10,10), censor.times = c(365,365,365,365), accelvar.names = c("DegreesC","RH"), describe.string = "DeviceR Simple Plan") print(DeviceR.altplan)
Compute the fisher and vcv matrices
ALT.vcv(DeviceR.altplan,DeviceR.Weibull.altpv)
compute the large-sample approximate precision (R) factors
evaluate(DeviceR.altplan, DeviceR.Weibull.altpv,quantile.of.interest=c(.1,.5))
sample size needed for a given value of R
plot(DeviceR.altplan, DeviceR.Weibull.altpv) SMRD:::plot.alt.sample.size(DeviceR.altplan, DeviceR.Weibull.altpv) ## simulate the ALT plans with option to see detail on some experiments DeviceR.sim.out <- ALTsim(DeviceR.altplan, DeviceR.Weibull.altpv, number.sim = 400, show.detail.on = 5) DeviceR.sim.out <- ALTsim(DeviceR.altplan, DeviceR.Weibull.altpv, number.sim = 400, show.detail.on = 0) ## simulate the ALT plans and plot summary DeviceR.sim.out <- simulate(DeviceR.altplan, ALT.plan.values = DeviceR.Weibull.altpv, nsim = 400, show.detail.on = 5) DeviceR.sim.out <- simulate(DeviceR.altplan, ALT.plan.values = DeviceR.Weibull.altpv, nsim = 400, show.detail.on = 0) ## plot the ALT simulation results ALT.plot.time.v.x(DeviceR.sim.out) ALT.plot.time.v.x(DeviceR.sim.out, focus.variable = 2) ALT.plot.time.v.x(DeviceR.sim.out, x.of.interest = c(25,10), xlim = c(20,80)) ALT.plot.FracFail.v.Time(DeviceR.sim.out) ALT.plot.FracFail.v.Time(DeviceR.sim.out, x.of.interest = c(25,10), xlim = c(100,10000)) ## look at joint and marginal disributions of focus quantities summarize.simultation.results(DeviceR.sim.out, "Joint and Marginal", focus.quantity1 = "quantile", focus.quantity.detail1 = 0.1, x.of.interest1 = "60;20", focus.quantity2 = "parameter", focus.quantity.detail2 = 3, x.of.interest2 = NA, plot.type = "density") summarize.simultation.results(DeviceR.sim.out, "Marginal only", focus.quantity1 = "quantile", focus.quantity.detail1 = 0.1, x.of.interest1 = "60;20", focus.quantity2 = "parameter", focus.quantity.detail2 = 3, x.of.interest2 = NA) summarize.simultation.results(DeviceR.sim.out, "Marginal only", focus.quantity1 = "quantile", focus.quantity.detail1 = 0.1, x.of.interest1 = "60;20", focus.quantity2 = "parameter", focus.quantity.detail2 = 1, x.of.interest2 = NA, plot.type = "density") summarize.simultation.results(DeviceR.sim.out, "Joint and Marginal", focus.quantity1 = "quantile", focus.quantity.detail1 = 0.1, x.of.interest1 = "60;20", focus.quantity2 = "parameter", focus.quantity.detail2 = 2, x.of.interest2 = NA, plot.type = "density") summarize.simultation.results(DeviceR.sim.out, "Joint only", focus.quantity1 = "quantile", focus.quantity.detail1 = 0.1, x.of.interest1 = "60;20", focus.quantity2 = "parameter", focus.quantity.detail2 = 4, x.of.interest2 = NA)
NelsonInsulation example from page 350 of Nelson (1990) and Escobar and Meeker (1995) and Meeker and Escobar (1998) page 548
define two-variable planning values
NelsonInsulation.Weibull.altpv <- get.alt.plan.values.from.slope.and.point(distribution = "Weibull", slope= c(-12.28,-1.296), relationship = c("log","log"), accelvar.units = c("vpm","cm"), time.units = "Hours", censor.time = 1000, probs = c(1.8e-6), accelvar = c(80,.266), beta = 1/.6734, use.conditions = c(80,.266)) print(NelsonInsulation.Weibull.altpv) ## define two-variable ALT test plans levels = cbind(c(120,120,120,150,150,150,175,175,175,200,200,200), c(.163,.266,.355,.163,.266,.355,.163,.266,.355,.163,.266,.355)) units = c(11,18,11,8,14,8,8,14,8,11,18,11) NelsonInsulation.altplan <- get.alt.test.plan.direct(accel.variable.levels = levels, number.of.units = units, censor.times = rep(1000,12), accelvar.names = c("Volts per mm","Thick"), describe.string = "NelsonInsulation Factorial Plan") print(NelsonInsulation.altplan) print(NelsonInsulation.Weibull.altpv) ## compute the fisher and vcv matrices ALT.vcv(NelsonInsulation.altplan, NelsonInsulation.Weibull.altpv) ## compute the large-sample approximate precision (R) factors evaluate(NelsonInsulation.altplan, NelsonInsulation.Weibull.altpv, quantile.of.interest = c(.1,.5)) evaluate(NelsonInsulation.altplan, NelsonInsulation.Weibull.altpv, use.conditions = c(175,.163), quantile.of.interest = c(.1,.5)) evaluate(NelsonInsulation.altplan, NelsonInsulation.Weibull.altpv, use.conditions = c(100,.1), quantile.of.interest = c(.1,.5)) ## sample size needed for a given value of R SMRD:::plot.alt.sample.size(NelsonInsulation.altplan, NelsonInsulation.Weibull.altpv) NelsonInsulation.sim.out <- ALTsim(NelsonInsulation.altplan, NelsonInsulation.Weibull.altpv, number.sim = 400, show.detail.on = 1) ALT.plot.time.v.x(NelsonInsulation.sim.out) ALT.plot.time.v.x(NelsonInsulation.sim.out, x.of.interest = c(100,.1), xlim = c(100,200)) ALT.plot.FracFail.v.Time(NelsonInsulation.sim.out) ALT.plot.FracFail.v.Time(NelsonInsulation.sim.out, x.of.interest = c(25,10), xlim = c(100,10000)) summarize.simultation.results(NelsonInsulation.sim.out, "Joint and Marginal", focus.quantity1 = "quantile", focus.quantity.detail1 = 0.1, x.of.interest1 = "100;.1", focus.quantity2 = "parameter", focus.quantity.detail2 = 3, x.of.interest2 = NA, plot.type = "density") ## examples using basic simulation routine test.matrix <- cbind(V1 = c(1,1,2,2),V2 = c(1,2,1,2)) altsim.out <- altsim(accel.var.mat = test.matrix, nsamsz = c(4,4,4,4), centim = c(40000,40000,40000,40000), theta = c(1,-24,5,1), distribution = "normal", number.sim = 10, debug = F) altsim.out <- altsim(accel.var.mat = as.matrix(c(1,2,3,4)), nsamsz = c(4,4,4,4), centim = c(200,200,200,200), theta = c(1,-2,3), distribution = "normal", number.sim = 5, debug = F, kprint = 0) altsimReturnFrame(accel.var.mat = test.matrix, nsamsz = c(4,4,4,4), centim = c(100,100,100,100), theta = c(1,1,1,2), distribution =" lognormal", relationship = c("linear","log")) ## Simulate a single ALT data set altsimReturnFrame(accel.var.mat = test.matrix, nsamsz = c(4,4,4,4), centim = c(100,100,100,100), theta = c(1,1,1,2), distribution = "lognormal", relationship = c("linear","log")) ## example of multiple minima varone.grid(a = -0.9, b1 = -7.9, perc = 0.01, xlab = "xiL", ylab = "piL", xiL.lower = -1, levels = c(.001,.01,0.10000000000000001, 0.20000000000000001, 0.5, 1, 2), dump = T)
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