Description Usage Arguments Value References See Also Examples
altopt.rc
creates D, U or I optimal design
of the accelerated life testing with right censoring plan.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 |
optType |
the choice of |
N |
the number of test units. |
tc |
the censoring time. |
nf |
the number of stress factors. |
alpha |
the value of the shape parameter of Weibull distribution. |
formula |
the object of class formula which is the linear predictor model. |
coef |
the numeric vector containing the coefficients of each term in |
useCond |
the numeric vector of use condition.
It should be provided when |
useLower |
the numeric vector of lower bound of use region.
It should be provided when |
useUpper |
the numeric vector of upper bound of use region.
It should be provided when |
nOpt |
the number of repetition of optimization process. Default is 1. |
nKM |
the number of repetition of k-means clustering. Default is 20. |
nCls |
the number of clusters used for k-means clustering. If not specified, it is set as the number of parameters in the linear predictor model. |
A list with components
call: the matched call.
opt.design.ori: the original optimal design.
opt.value.ori: the objective function value of opt.design.ori
.
opt.design.rounded: the optimal design clustered by rounding in third decimal points.
opt.value.rounded: the objective function value of opt.design.rounded
.
opt.design.kmeans: the optimal design clustered by kmeans
.
opt.value.kmeans: the objective function value of opt.design.kmeans
.
Monroe, E. M., Pan, R., Anderson-Cook, C. M., Montgomery, D. C. and Borror C. M. (2011) A Generalized Linear Model Approach to Designing Accelerated Life Test Experiments, Quality and Reliability Engineering International 27(4), 595–607
Yang, T., Pan, R. (2013) A Novel Approach to Optimal Accelerated Life Test Planning With Interval Censoring, Reliability, IEEE Transactions on 62(2), 527–536
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 | ## Not run:
# Generating D optimal design for right censoring.
altopt.rc("D", 100, 100, 2, 1, formula = ~ x1 + x2 + x1:x2,
coef = c(0, -4.086, -1.476, 0.01))
# Generating U optimal design for right censoring.
altopt.rc("D", 100, 100, 2, 1, formula = ~ x1 + x2 + x1:x2,
coef = c(0, -4.086, -1.476, 0.01), useCond = c(1.758, 3.159))
# Generating I optimal design for right censoring.
altopt.rc("D", 100, 100, 2, 1, formula = ~ x1 + x2 + x1:x2,
coef = c(0, -4.086, -1.476, 0.01), useLower = c(1.458, 2.859),
useUpper = c(2.058, 3.459))
## End(Not run)
|
$call
altopt.rc(optType = "D", N = 100, tc = 100, nf = 2, alpha = 1,
formula = ~x1 + x2 + x1:x2, coef = c(0, -4.086, -1.476, 0.01))
$opt.design.ori
x1 x2 allocation
1 0.0000000 0 21
2 1.0000000 0 28
3 0.0000000 1 21
4 0.7943848 1 3
5 0.7943848 1 1
6 0.7943848 1 4
7 0.7943848 1 1
8 0.7943848 1 17
9 0.7943848 1 1
10 0.7943848 1 1
11 0.7943848 1 1
12 0.7943848 1 1
$opt.value.ori
[1] 112649.9
$opt.design.rounded
x1 x2 allocation
1 0.000 0 21
2 1.000 0 28
3 0.000 1 21
4 0.794 1 30
$opt.value.rounded
[1] 112649.8
$opt.design.kmeans
x1 x2 allocation
1 0.0000000 1 21
2 0.7943848 1 30
3 1.0000000 0 28
4 0.0000000 0 21
$opt.value.kmeans
[1] 112649.9
$call
altopt.rc(optType = "D", N = 100, tc = 100, nf = 2, alpha = 1,
formula = ~x1 + x2 + x1:x2, coef = c(0, -4.086, -1.476, 0.01),
useCond = c(1.758, 3.159))
$opt.design.ori
x1 x2 allocation
1 1.0000000 -2.775558e-17 1
2 0.0000000 0.000000e+00 23
3 1.0000000 0.000000e+00 24
4 0.0000000 1.000000e+00 24
5 0.7943848 1.000000e+00 1
6 0.7943848 1.000000e+00 1
7 0.7943848 1.000000e+00 1
8 0.7943848 1.000000e+00 3
9 0.7943848 1.000000e+00 1
10 0.7943848 1.000000e+00 2
11 0.7943848 1.000000e+00 2
12 0.7943848 1.000000e+00 8
13 0.7943848 1.000000e+00 1
14 0.7943848 1.000000e+00 1
15 0.7943848 1.000000e+00 1
16 0.7943848 1.000000e+00 1
17 0.7943848 1.000000e+00 2
18 0.7943848 1.000000e+00 1
19 0.7943848 1.000000e+00 1
20 0.7943848 1.000000e+00 1
$opt.value.ori
[1] 117503.3
$opt.design.rounded
x1 x2 allocation
1 0.000 0 23
2 1.000 0 25
3 0.000 1 24
4 0.794 1 28
$opt.value.rounded
[1] 117503.2
$opt.design.kmeans
x1 x2 allocation
1 0.0000000 0.000000e+00 23
2 1.0000000 -1.110223e-18 25
3 0.0000000 1.000000e+00 24
4 0.7943848 1.000000e+00 28
$opt.value.kmeans
[1] 117503.3
$call
altopt.rc(optType = "D", N = 100, tc = 100, nf = 2, alpha = 1,
formula = ~x1 + x2 + x1:x2, coef = c(0, -4.086, -1.476, 0.01),
useLower = c(1.458, 2.859), useUpper = c(2.058, 3.459))
$opt.design.ori
x1 x2 allocation
1 0.0000000 0 20
2 1.0000000 0 23
3 0.0000000 1 24
4 0.7943848 1 5
5 0.7943848 1 5
6 0.7943848 1 2
7 0.7943848 1 1
8 0.7943848 1 1
9 0.7943848 1 3
10 0.7943848 1 2
11 0.7943848 1 1
12 0.7943848 1 7
13 0.7943848 1 1
14 0.7943848 1 1
15 0.7943848 1 1
16 0.7943848 1 2
17 0.7943848 1 1
$opt.value.ori
[1] 110788.8
$opt.design.rounded
x1 x2 allocation
1 0.000 0 20
2 1.000 0 23
3 0.000 1 24
4 0.794 1 33
$opt.value.rounded
[1] 110788.8
$opt.design.kmeans
x1 x2 allocation
1 0.0000000 0 20
2 0.7943848 1 33
3 1.0000000 0 23
4 0.0000000 1 24
$opt.value.kmeans
[1] 110788.8
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