search for: octan

I have two ideas about it. 1- i) Entering variables in quadratic form is done with the command I (variable ^ 2) - plsr (octane ~ NIR + I (nir ^ 2), ncomp = 10, data = gasTrain, validation = "LOO" You could also use a new variable NIR_sq <- (NIR) ^ 2 ii) To insert a square variable, use syntax I (x ^ 2) - it is very important to insert I before the parentheses. iii) If you want to make the interaction betwee...

Below. -- Bert Bert Gunter On Thu, Jul 13, 2017 at 3:07 AM, Luigi Biagini <luigi.biagini at gmail.com> wrote: > I have two ideas about it. > > 1- > i) Entering variables in quadratic form is done with the command I > (variable ^ 2) - > plsr (octane ~ NIR + I (nir ^ 2), ncomp = 10, data = gasTrain, validation = > "LOO" > You could also use a new variable NIR_sq <- (NIR) ^ 2 > > ii) To insert a square variable, use syntax I (x ^ 2) - it is very > important to insert I before the parentheses. True, but better I beli...

...Bert Gunter > > > > On Thu, Jul 13, 2017 at 3:07 AM, Luigi Biagini <luigi.biagini at gmail.com> wrote: >> I have two ideas about it. >> >> 1- >> i) Entering variables in quadratic form is done with the command I >> (variable ^ 2) - >> plsr (octane ~ NIR + I (nir ^ 2), ncomp = 10, data = gasTrain, validation = >> "LOO" >> You could also use a new variable NIR_sq <- (NIR) ^ 2 >> >> ii) To insert a square variable, use syntax I (x ^ 2) - it is very >> important to insert I before the parentheses. &gt...

...gt; >> On Thu, Jul 13, 2017 at 3:07 AM, Luigi Biagini <luigi.biagini at gmail.com> wrote: >>> I have two ideas about it. >>> >>> 1- >>> i) Entering variables in quadratic form is done with the command I >>> (variable ^ 2) - >>> plsr (octane ~ NIR + I (nir ^ 2), ncomp = 10, data = gasTrain, validation = >>> "LOO" >>> You could also use a new variable NIR_sq <- (NIR) ^ 2 >>> >>> ii) To insert a square variable, use syntax I (x ^ 2) - it is very >>> important to insert I before t...

...tting a linear model, I want to fit my data with a quadratic function with interaction terms. But I am not sure how. I will use an example to illustrate my problem: Following the example in the PLS manual: ## Read data data(gasoline) gasTrain <- gasoline[1:50,] ## Perform PLS gas1 <- plsr(octane ~ NIR, ncomp = 10, data = gasTrain, validation = "LOO") where octane ~ NIR is the model that this example is fitting with. NIR is a collective of variables, i.e. NIR spectra consists of 401 diffuse reflectance measurements from 900 to 1700 nm. Instead of fitting with predict.octane[i]...

...with interaction terms. But I am not sure >> how. I will use an example to illustrate my problem: >> >> Following the example in the PLS manual: >> ## Read data >> data(gasoline) >> gasTrain <- gasoline[1:50,] >> ## Perform PLS >> gas1 <- plsr(octane ~ NIR, ncomp = 10, data = gasTrain, validation = "LOO") >> >> where octane ~ NIR is the model that this example is fitting with. >> >> NIR is a collective of variables, i.e. NIR spectra consists of 401 diffuse >> reflectance measurements from 900 to 1700 nm....

...work if NIR is a matrix, not a data.frame. > The degree argument apparently *must* be explicitly named if NIR is > not a numeric vector. AFAICS, this is unclear or unstated in ?poly. I still get the same error with: library(pld) data(gasoline) gasTrain <- gasoline[1:50,] gas1 <- plsr(octane ~ poly(as.matrix(NIR), 2), ncomp = 10, data = gasTrain, validation = "LOO") Error in rep.int(rep.int(seq_len(nx), rep.int(rep.fac, nx)), orep) : invalid 'times' value > gas1 <- plsr(octane ~ poly(as.matrix(gasTrain$NIR), degree=2), ncomp = 10, data = gasTrain, validat...

...data with a quadratic function with interaction terms. But I am not sure > how. I will use an example to illustrate my problem: > > Following the example in the PLS manual: > ## Read data > data(gasoline) > gasTrain <- gasoline[1:50,] > ## Perform PLS > gas1 <- plsr(octane ~ NIR, ncomp = 10, data = gasTrain, validation = "LOO") > > where octane ~ NIR is the model that this example is fitting with. > > NIR is a collective of variables, i.e. NIR spectra consists of 401 diffuse > reflectance measurements from 900 to 1700 nm. > > Instea...

...> The build was successful with out any runtime faliures, here are few > stats: > > This is very good, thanks for working on this. > > > > > Measure W/O IPRA WITH IPRA > > ======= ======== ========= > > Total Build Time 76 mins 82.3 mins 8% increment > > Octane v2.0 JS Benchmark Score (higher is better) 18675.69 19665.16 5% > > improvement > > This speedup is kind of amazing, enough to make me a little bit suspicious. > From what I can see, Octane is not exactly a microbenchmark but tries > to model complex/real-world web applications,...

...fails to create device inodes to a NFS mounted filesystem. rsync via ssh, client side is on IRIX 6.5.19, server side is on RedHat Linux 7.3 (rsync 2.5.4 protocol version 26) and the NFS mount is from a linux box (NFSv3 and dev,suid as mount options, no_root_squash,rw as export option). [root@octane /]# /usr/freeware/bin/rsync -aHzvxe "ssh -q" --delete --rsync-path=/usr/bin/rsync root@host:/ /net/ente/master/DISK [...] mknod dev/zqft0 : Invalid argument mknod dev/zqft1 : Invalid argument mknod dev/zqft2 : Invalid argument mknod dev/zqft3 : Invalid argument [...] mknod by commandli...

Hello, I build FireFox-46.0.1 source with llvm to test interprocedural register allocation. The build was successful with out any runtime faliures, here are few stats: Measure W/O IPRA WITH IPRA ======= ======== ========= Total Build Time 76 mins 82.3 mins 8% increment Octane v2.0 JS Benchmark Score (higher is better) 18675.69 19665.16 5% improvement Kraken JS Benchmark time (lower is better) 1416.2 ms 1421.3 ms 0.35% regression JetStream JS Benchmark Score (higer is better) 110.10 112.88 2.52% improvement Any suggestions are welcome on how to effectively measure per...

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...thanks in advanced by some help! Thanks. Cleber ############### > > ### example code: > library( earth ) > data( gasoline, package='pls' ) > > nir <- gasoline$NIR > dim( nir ) [1] 60 401 > class( nir ) [1] "AsIs" > > oct <- gasoline$octane > > mars <- earth( oct ~ nir, nk=300, nfold=10, degree=3, trace=0 ) > > plotmo( mars ) Error: bad index (missing column in x?) > plotmo( mars, all1=T ) Error: bad index (missing column in x?) > plotmo( mars, all1=T, all2=T ) Error: bad index (missing column in x?) &gt...

...not sure >>> how. I will use an example to illustrate my problem: >>> >>> Following the example in the PLS manual: >>> ## Read data >>> data(gasoline) >>> gasTrain <- gasoline[1:50,] >>> ## Perform PLS >>> gas1 <- plsr(octane ~ NIR, ncomp = 10, data = gasTrain, validation = "LOO") >>> >>> where octane ~ NIR is the model that this example is fitting with. >>> >>> NIR is a collective of variables, i.e. NIR spectra consists of 401 diffuse >>> reflectance measurement...

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Hi, I enabled password encryption and NT clients were able to connect. However, Windows 95 users were not able to connect any more unless they use smbpassword to reset the password (it's not an acceptable solution for our environment). If I used "update encrypted = yes", "encrypt passwords" then Windows 95 users can login with NIS password but not for NT users. How to

...independent (X) variables such as chemometric datasets there is a convenient formula and dataframe construction that allows one to access the entire X matrix with a single term. Consider the gasoline dataset available in the pls package. For the model statement in the plsr function one can write: Octane ~ NIR NIR refers to a (wide) matrix which is a portion of a dataframe. The naming of the columns is of the form: 'NIR.xxxx nm' names(gasoline) returns... $names [1] "octane" "NIR" instead of... $names [1] "octane" "NIR.1000 nm" "NIR.1001...

...I will use an example to illustrate my problem: >>>> >>>> Following the example in the PLS manual: >>>> ## Read data >>>> data(gasoline) >>>> gasTrain <- gasoline[1:50,] >>>> ## Perform PLS >>>> gas1 <- plsr(octane ~ NIR, ncomp = 10, data = gasTrain, validation = "LOO") >>>> >>>> where octane ~ NIR is the model that this example is fitting with. >>>> >>>> NIR is a collective of variables, i.e. NIR spectra consists of 401 diffuse >>>> refle...

...playingwithpointers.com> wrote: > Hi Vivek, > > [Dropping firefox-dev, since I don't want to spam them] > > vivek pandya via llvm-dev wrote: > > Measure W/O IPRAWITH IPRA > > ======================== > > Total Build Time76 mins82.3 mins8% increment > > Octane v2.0 JS Benchmark Score (higher is better)18675.69 19665.165% > improvement > > Kraken JS Benchmark time (lower is better)1416.2 ms 1421.3 ms 0.35% > regression > > JetStream JS Benchmark Score (higer is better)110.10112.882.52% > improvement > > This is great! > >...

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