D-optimum design - optimization model in R

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D-optimum design - optimization model in R

Thanh Tran
Dear all,



I'm trying to use the D-optimum design. In my data, the response is KIC,
and 4 factors are AC, AV, T, and Temp. A typical second-degree response
modeling is as follows:



> data<-read.csv("2.csv", header =T)

> mod <-
lm(KIC~AC+I(AC^2)+AV+I(AV^2)+T+I(T^2)+Temp+I(Temp^2)+AC:AV+AC:T+AC:Temp+AV:T+AV:Temp+T:Temp,

+ data = data)



The result of the model:



KIC = 4.85 – 2.9AC +0.151 AV + 0.1094T

          + 0.0091Temp + 0.324 AC^2-0.0156V^2

          - 10.00106T^2 - 0.0009Temp^2 + 0.0071AC´AV

          - 0.00087AC´T -0.00083AC´Temp – 0.0018AV´T

         +0.0015AV´Temp – 0.000374 AV ´ T



Based on the above response modelling, I want to determine levels of the
AC, AV, T, and Temp to have the Maximum value of KIC. The result running in
Minitab as is shown in Figure 1. In R, I try to compute an D-optimum design
with the following codes:



> attach(data)

> F.trig <- F.cube

> F.trip <-
F.cube(KIC~AC+I(AC^2)+AV+I(AV^2)+T+I(T^2)+Temp+I(Temp^2)+AC:AV+AC:T+AC:Temp+AV:T+AV:Temp+T:Temp,

+ c(4,4,30,5), # Smalesst values of AC,AV,T, and Temp

+ c(5,7,50,25), # Highest values of AC,AV,T, and Temp

+ c(3,3,3,3)) # Numbers of levels ofAC,AV,T, and Temp

> res.trip.D <- od.AA(F.trip,1,alg = "doom", crit = "D",

+ graph =1:7, t.max = 4)



I have the result as shown in Figure 2 but I cannot find out the optimum
design as shown in Figure 1 using Minitab.



If anyone has any experience about what would be the reason for error or
how I can solve it? I really appreciate your support and help.



Best regards,

Nhat Tran



Ps: I also added a CSV file for practicing R.

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Re: D-optimum design - optimization model in R

Bert Gunter-2
Please do not re-post. To increase your chance of getting a useful answer,
read and follow the posting guide below, which you have not yet done. For
example, what is "F.cube", what packages are you using? Also, this list is
about R programming, not statistics, which is more what your query seems to
be about. Finally, search yourself! -- e,g, "d-optimal designs" on rseek.org
brought up what appeared to be many relevant hits, including a CRAN task
view on experimental design.

Bert Gunter

"The trouble with having an open mind is that people keep coming along and
sticking things into it."
-- Opus (aka Berkeley Breathed in his "Bloom County" comic strip )


On Tue, Dec 4, 2018 at 3:29 AM Thanh Tran <[hidden email]> wrote:

> Dear all,
>
>
>
> I'm trying to use the D-optimum design. In my data, the response is KIC,
> and 4 factors are AC, AV, T, and Temp. A typical second-degree response
> modeling is as follows:
>
>
>
> > data<-read.csv("2.csv", header =T)
>
> > mod <-
>
> lm(KIC~AC+I(AC^2)+AV+I(AV^2)+T+I(T^2)+Temp+I(Temp^2)+AC:AV+AC:T+AC:Temp+AV:T+AV:Temp+T:Temp,
>
> + data = data)
>
>
>
> The result of the model:
>
>
>
> KIC = 4.85 – 2.9AC +0.151 AV + 0.1094T
>
>           + 0.0091Temp + 0.324 AC^2-0.0156V^2
>
>           - 10.00106T^2 - 0.0009Temp^2 + 0.0071AC´AV
>
>           - 0.00087AC´T -0.00083AC´Temp – 0.0018AV´T
>
>          +0.0015AV´Temp – 0.000374 AV ´ T
>
>
>
> Based on the above response modelling, I want to determine levels of the
> AC, AV, T, and Temp to have the Maximum value of KIC. The result running in
> Minitab as is shown in Figure 1. In R, I try to compute an D-optimum design
> with the following codes:
>
>
>
> > attach(data)
>
> > F.trig <- F.cube
>
> > F.trip <-
>
> F.cube(KIC~AC+I(AC^2)+AV+I(AV^2)+T+I(T^2)+Temp+I(Temp^2)+AC:AV+AC:T+AC:Temp+AV:T+AV:Temp+T:Temp,
>
> + c(4,4,30,5), # Smalesst values of AC,AV,T, and Temp
>
> + c(5,7,50,25), # Highest values of AC,AV,T, and Temp
>
> + c(3,3,3,3)) # Numbers of levels ofAC,AV,T, and Temp
>
> > res.trip.D <- od.AA(F.trip,1,alg = "doom", crit = "D",
>
> + graph =1:7, t.max = 4)
>
>
>
> I have the result as shown in Figure 2 but I cannot find out the optimum
> design as shown in Figure 1 using Minitab.
>
>
>
> If anyone has any experience about what would be the reason for error or
> how I can solve it? I really appreciate your support and help.
>
>
>
> Best regards,
>
> Nhat Tran
>
>
>
> Ps: I also added a CSV file for practicing R.
> ______________________________________________
> [hidden email] mailing list -- To UNSUBSCRIBE and more, see
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide
> http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
>

        [[alternative HTML version deleted]]

______________________________________________
[hidden email] mailing list -- To UNSUBSCRIBE and more, see
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
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Re: D-optimum design - optimization model in R

Thanh Tran
Dear  Bert Gunter,

Thank you for your advice. I will take care in the next post.

Best regards,
Nhat Tran.

Vào Th 3, 4 thg 12, 2018 vào lúc 23:16 Bert Gunter <[hidden email]>
đã viết:

> Please do not re-post. To increase your chance of getting a useful answer,
> read and follow the posting guide below, which you have not yet done. For
> example, what is "F.cube", what packages are you using? Also, this list is
> about R programming, not statistics, which is more what your query seems to
> be about. Finally, search yourself! -- e,g, "d-optimal designs" on
> rseek.org brought up what appeared to be many relevant hits, including a
> CRAN task view on experimental design.
>
> Bert Gunter
>
> "The trouble with having an open mind is that people keep coming along and
> sticking things into it."
> -- Opus (aka Berkeley Breathed in his "Bloom County" comic strip )
>
>
> On Tue, Dec 4, 2018 at 3:29 AM Thanh Tran <[hidden email]> wrote:
>
>> Dear all,
>>
>>
>>
>> I'm trying to use the D-optimum design. In my data, the response is KIC,
>> and 4 factors are AC, AV, T, and Temp. A typical second-degree response
>> modeling is as follows:
>>
>>
>>
>> > data<-read.csv("2.csv", header =T)
>>
>> > mod <-
>>
>> lm(KIC~AC+I(AC^2)+AV+I(AV^2)+T+I(T^2)+Temp+I(Temp^2)+AC:AV+AC:T+AC:Temp+AV:T+AV:Temp+T:Temp,
>>
>> + data = data)
>>
>>
>>
>> The result of the model:
>>
>>
>>
>> KIC = 4.85 – 2.9AC +0.151 AV + 0.1094T
>>
>>           + 0.0091Temp + 0.324 AC^2-0.0156V^2
>>
>>           - 10.00106T^2 - 0.0009Temp^2 + 0.0071AC´AV
>>
>>           - 0.00087AC´T -0.00083AC´Temp – 0.0018AV´T
>>
>>          +0.0015AV´Temp – 0.000374 AV ´ T
>>
>>
>>
>> Based on the above response modelling, I want to determine levels of the
>> AC, AV, T, and Temp to have the Maximum value of KIC. The result running
>> in
>> Minitab as is shown in Figure 1. In R, I try to compute an D-optimum
>> design
>> with the following codes:
>>
>>
>>
>> > attach(data)
>>
>> > F.trig <- F.cube
>>
>> > F.trip <-
>>
>> F.cube(KIC~AC+I(AC^2)+AV+I(AV^2)+T+I(T^2)+Temp+I(Temp^2)+AC:AV+AC:T+AC:Temp+AV:T+AV:Temp+T:Temp,
>>
>> + c(4,4,30,5), # Smalesst values of AC,AV,T, and Temp
>>
>> + c(5,7,50,25), # Highest values of AC,AV,T, and Temp
>>
>> + c(3,3,3,3)) # Numbers of levels ofAC,AV,T, and Temp
>>
>> > res.trip.D <- od.AA(F.trip,1,alg = "doom", crit = "D",
>>
>> + graph =1:7, t.max = 4)
>>
>>
>>
>> I have the result as shown in Figure 2 but I cannot find out the optimum
>> design as shown in Figure 1 using Minitab.
>>
>>
>>
>> If anyone has any experience about what would be the reason for error or
>> how I can solve it? I really appreciate your support and help.
>>
>>
>>
>> Best regards,
>>
>> Nhat Tran
>>
>>
>>
>> Ps: I also added a CSV file for practicing R.
>> ______________________________________________
>> [hidden email] mailing list -- To UNSUBSCRIBE and more, see
>> https://stat.ethz.ch/mailman/listinfo/r-help
>> PLEASE do read the posting guide
>> http://www.R-project.org/posting-guide.html
>> and provide commented, minimal, self-contained, reproducible code.
>>
>

        [[alternative HTML version deleted]]

______________________________________________
[hidden email] mailing list -- To UNSUBSCRIBE and more, see
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.