Hi > data(gasoline) > str(gasoline) 'data.frame': 60 obs. of 2 variables: $ octane: num 85.3 85.2 88.5 83.4 87.9 ... $ NIR : AsIs [1:60, 1:401] -0.050193 -0.044227 -0.046867 -0.046705 -0.050859 ... ..- attr(*, "dimnames")=List of 2 .. ..$ : chr "1" "2" "3" "4" ... .. ..$ : chr "900 nm" "902 nm" "904 nm" "906 nm" ... > str(gasoline$NIR) AsIs [1:60, 1:401] -0.050193 -0.044227 -0.046867 -0.046705 -0.050859 ... - attr(*, "dimnames")=List of 2 ..$ : chr [1:60] "1" "2" "3" "4" ... ..$ : chr [1:401] "900 nm" "902 nm" "904 nm" "906 nm" ... > is.matrix(gasoline$NIR) [1] TRUE
so the second element of gasoline data frame is a matrix > ?AsIs > df<-data.frame(x=1:5, I(matrix(rnorm(10), 5,2))) > df x matrix.rnorm.10...5..2..1 matrix.rnorm.10...5..2..2 1 1 0.187703.... 0.213312.... 2 2 -0.66264.... -0.47941.... 3 3 -0.82334.... -0.04324.... 4 4 -0.37255.... 0.883027.... 5 5 -0.28700.... -1.03431.... > str(df) 'data.frame': 5 obs. of 2 variables: $ x : int 1 2 3 4 5 $ matrix.rnorm.10...5..2.: AsIs [1:5, 1:2] 0.187703.... -0.66264.... -0.82334.... -0.37255.... -0.28700.... ... > Regards Petr r-help-boun...@r-project.org napsal dne 23.10.2009 18:43:56: > > I have read that one ,I want to this method to be used to my data.but I donot > know how to put my data into R. > > James W. MacDonald wrote: > > > > > > > > bbslover wrote: > >> > >> > >> Steve Lianoglou-6 wrote: > >>> Hi, > >>> > >>> On Oct 22, 2009, at 2:35 PM, bbslover wrote: > >>> > >>>> Usage > >>>> data(gasoline) > >>>> Format > >>>> A data frame with 60 observations on the following 2 variables. > >>>> octane > >>>> a numeric vector. The octane number. > >>>> NIR > >>>> a matrix with 401 columns. The NIR spectrum > >>>> > >>>> and I see the gasoline data to see below > >>>> NIR.1686 nm NIR.1688 nm NIR.1690 nm NIR.1692 nm NIR.1694 nm NIR.1696 > >>>> nm > >>>> NIR.1698 nm NIR.1700 nm > >>>> 1 1.242645 1.250789 1.246626 1.250985 1.264189 1.244678 1.245913 > >>>> 1.221135 > >>>> 2 1.189116 1.223242 1.253306 1.282889 1.215065 1.225211 1.227985 > >>>> 1.198851 > >>>> 3 1.198287 1.237383 1.260979 1.276677 1.218871 1.223132 1.230321 > >>>> 1.208742 > >>>> 4 1.201066 1.233299 1.262966 1.272709 1.211068 1.215044 1.232655 > >>>> 1.206696 > >>>> 5 1.259616 1.273713 1.296524 1.299507 1.226448 1.230718 1.232864 > >>>> 1.202926 > >>>> 6 1.24109 1.262138 1.288401 1.291118 1.229769 1.227615 1.22763 > >>>> 1.207576 > >>>> 7 1.245143 1.265648 1.274731 1.292441 1.218317 1.218147 1.222273 > >>>> 1.200446 > >>>> 8 1.222581 1.245782 1.26002 1.290305 1.221264 1.220265 1.227947 > >>>> 1.188174 > >>>> 9 1.234969 1.251559 1.272416 1.287405 1.211995 1.213263 1.215883 > >>>> 1.196102 > >>>> > >>>> look at this NIR.1686 nm NIR.1688 nm NIR.1690 nm NIR.1692 nm NIR. > >>>> 1694 nm > >>>> NIR.1696 nm NIR.1698 nm NIR.1700 nm > >>>> > >>>> how can I add letters NIR to my variable, because my 600 > >>>> independents never > >>>> have NIR as the prefix. however, it is needed to model the plsr. for > >>>> example aa=plsr(y~NIR, data=data ,....), the prefix NIR is > >>>> necessary, how > >>>> can I do with it? > >>> I'm not really sue that I'm getting you, but if your problem is that > >>> the column names of your data.frame don't match the variable names > >>> you'd like to use in your formula, just change the colnames of your > >>> data.frame to match your formula. > >>> > >>> BTW - I have no idea where to get this gasoline data set, so I'm just > >>> imagining: > >>> > >>> eg. > >>> colnames(gasoline) <- c('put', 'the', 'variable', 'names', 'that', > >>> 'you', 'want', 'here') > >>> > >>> -steve > >>> > >>> -- > >>> Steve Lianoglou > >>> Graduate Student: Computational Systems Biology > >>> | Memorial Sloan-Kettering Cancer Center > >>> | Weill Medical College of Cornell University > >>> Contact Info: http://cbio.mskcc.org/~lianos/contact > >>> > >>> ______________________________________________ > >>> R-help@r-project.org mailing list > >>> 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. > >>> > >>> > >> > >> thanks for you. but the numbers of indenpendence are so many, it is not > >> easy > >> to identify them one by one, is there some better way? > > > > You don't need to identify anything. What you need to do is read the > > help page for the function you want to use, so you (at the very least) > > know how to use the function. > > > > > library(pls) > > > data(gasoline) > > > fit <- plsr(octane~NIR, data=gasoline, validation = "CV") > > > summary(fit) > > Data: X dimension: 60 401 > > Y dimension: 60 1 > > Fit method: kernelpls > > Number of components considered: 53 > > > > VALIDATION: RMSEP > > Cross-validated using 10 random segments. > > (Intercept) 1 comps 2 comps 3 comps 4 comps 5 comps 6 comps > > CV 1.543 1.372 0.3827 0.2522 0.2347 0.2455 0.2281 > > adjCV 1.543 1.367 0.3740 0.2497 0.2360 0.2407 0.2243 > > 7 comps 8 comps 9 comps 10 comps 11 comps 12 comps 13 comps > > CV 0.2311 0.2352 0.2455 0.2534 0.2737 0.2814 0.2832 > > adjCV 0.2257 0.2303 0.2395 0.2473 0.2646 0.2705 0.2726 > > 14 comps 15 comps 16 comps 17 comps 18 comps 19 comps 20 > > comps > > CV 0.2913 0.2932 0.2985 0.3137 0.3289 0.3323 > > 0.3391 > > adjCV 0.2808 0.2821 0.2863 0.3008 0.3141 0.3172 > > 0.3228 > > 21 comps 22 comps 23 comps 24 comps 25 comps 26 comps 27 > > comps > > CV 0.3476 0.3384 0.3316 0.3213 0.3155 0.3118 > > 0.3062 > > adjCV 0.3307 0.3217 0.3154 0.3057 0.3002 0.2964 > > 0.2908 > > 28 comps 29 comps 30 comps 31 comps 32 comps 33 comps 34 > > comps > > CV 0.3033 0.3034 0.3074 0.3083 0.3094 0.3087 > > 0.3105 > > adjCV 0.2881 0.2881 0.2917 0.2926 0.2936 0.2929 > > 0.2946 > > 35 comps 36 comps 37 comps 38 comps 39 comps 40 comps 41 > > comps > > CV 0.3108 0.3106 0.3105 0.3104 0.3104 0.3105 > > 0.3105 > > adjCV 0.2949 0.2947 0.2946 0.2945 0.2945 0.2945 > > 0.2946 > > 42 comps 43 comps 44 comps 45 comps 46 comps 47 comps 48 > > comps > > CV 0.3105 0.3105 0.3105 0.3105 0.3105 0.3105 > > 0.3105 > > adjCV 0.2946 0.2946 0.2946 0.2946 0.2946 0.2946 > > 0.2946 > > 49 comps 50 comps 51 comps 52 comps 53 comps > > CV 0.3105 0.3105 0.3105 0.3105 0.3105 > > adjCV 0.2946 0.2946 0.2946 0.2946 0.2946 > > > > TRAINING: % variance explained > > 1 comps 2 comps 3 comps 4 comps 5 comps 6 comps 7 comps > > 8 comps > > X 70.97 78.56 86.15 95.4 96.12 96.97 97.32 > > 98.1 > > octane 31.90 94.66 97.71 98.0 98.68 98.93 99.06 > > 99.1 > > 9 comps 10 comps 11 comps 12 comps 13 comps 14 comps 15 > > comps > > X 98.32 98.71 98.84 99.00 99.21 99.46 > > 99.52 > > octane 99.20 99.24 99.36 99.44 99.49 99.51 > > 99.58 > > 16 comps 17 comps 18 comps 19 comps 20 comps 21 comps 22 > > comps > > X 99.57 99.64 99.68 99.76 99.78 99.82 > > 99.84 > > octane 99.65 99.69 99.78 99.81 99.86 99.89 > > 99.92 > > 23 comps 24 comps 25 comps 26 comps 27 comps 28 comps 29 > > comps > > X 99.88 99.91 99.92 99.93 99.94 99.95 > > 99.96 > > octane 99.93 99.94 99.95 99.97 99.98 99.99 > > 99.99 > > 30 comps 31 comps 32 comps 33 comps 34 comps 35 comps 36 > > comps > > X 99.96 99.97 99.97 99.98 99.98 99.98 > > 99.98 > > octane 99.99 100.00 100.00 100.00 100.00 100.00 > > 100.00 > > 37 comps 38 comps 39 comps 40 comps 41 comps 42 comps 43 > > comps > > X 99.99 99.99 99.99 99.99 100 100 > > 100 > > octane 100.00 100.00 100.00 100.00 100 100 > > 100 > > 44 comps 45 comps 46 comps 47 comps 48 comps 49 comps 50 > > comps > > X 100 100 100 100 100 100 > > 100 > > octane 100 100 100 100 100 100 > > 100 > > 51 comps 52 comps 53 comps > > X 100 100 100 > > octane 100 100 100 > > > > > >> > >> > > > > -- > > James W. MacDonald, M.S. > > Biostatistician > > Douglas Lab > > University of Michigan > > Department of Human Genetics > > 5912 Buhl > > 1241 E. Catherine St. > > Ann Arbor MI 48109-5618 > > 734-615-7826 > > > > ______________________________________________ > > R-help@r-project.org mailing list > > 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. > > > > > > -- > View this message in context: http://www.nabble.com/data-frame-is-killing-me% > 21-help-tp26015079p26029667.html > Sent from the R help mailing list archive at Nabble.com. > > ______________________________________________ > R-help@r-project.org mailing list > 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. ______________________________________________ R-help@r-project.org mailing list 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.