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. -------------- next part -------------- A non-text attachment was scrubbed... Name: 2.png Type: image/png Size: 14594 bytes Desc: not available URL: <https://stat.ethz.ch/pipermail/r-help/attachments/20181204/8168a093/attachment.png>
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 <masternhattt at gmail.com> 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. > ______________________________________________ > R-help at r-project.org 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]]
Dear Bert Gunter, Thank you for your advice. I will take care in the next post. Best regards, Nhat Tran. V?o Th 3, 4 thg 12, 2018 va?o lu?c 23:16 Bert Gunter <bgunter.4567 at gmail.com> ?? vi?t:> 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 <masternhattt at gmail.com> 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. >> ______________________________________________ >> R-help at r-project.org 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]]