search for: mvr

Dear developeRs, I maintain a package 'pls', which has a main fit function mvr(), and functions plsr() and pcr() which are meant to take the same arguments as mvr() and do exactly the same, but have different default values for the 'method' argument. The three functions are all exported from the name space. In the 'pre namespace' era, I took inspiration from...

All, I have been using a data set to build pls models for three different soil properties. Two of the three models run fine; however I receive the following error for the final model. > libs.IC.cal <- mvr(libs.IC.fmla, data = libsdata.cond.cal, ncomp=20,validation = "LOO", method = "oscorespls") Error in colMeans(x, n, prod(dn), na.rm) : 'x' must be numeric There are many "0" for this soil property. Could this cause the error? Best, Ross *********...

...0.458 0.910 88.322 9.868 1.0746 13 11 201.228 0.910 89.202 10.328 1.0514 14 12 199.160 0.920 90.126 2.088 1.1326 15 13 135.540 0.786 121.506 19.140 0.6934 2 14 296.272 0.864 130.896 22.614 0.9104 6 15 190.766 0.840 108.050 7.336 0.8210 8 I have used the following sentence. b.pls<-mvr(q~w+c+d+r+o,data=b,method="simpls") > coef.mvr(b.pls) , , 5 comps q w 0.01993749 c 12.42713250 d -0.12050551 r -0.20287088 o 9.63670488 I have found that the sign of each component still cannot be explained by the reality. For instance, the sign of w should...

What version of R, what version of pls.pcr, and on what OS? Have you checked whether your versions of software are up to date? I get: > n <- 1350 > p <- 180 > y <- rnorm(n) > x <- matrix(sample(0:1, n*p, replace=TRUE), n, p) > fit <- mvr(x, y, method="SIMPLS", validat="none", ncomp=2) > xt <- matrix(sample(0:1, 312*p, replace=TRUE), 312, p) > yt <- predict(fit, xt) Andy > From: Stewart T Chang > > Greetings, > > I've encountered an error message while using the pls.pcr package...

Hello, I am trying to understand how to utilize the "mvr" function in the pls Package of R. I am utilizing the R "pls Package" document dated 18 May 2005 as guidance. My data set consists of a 12 x 12 data frame created from reading in a table of values. I have read the data in via the command: volumes <- read.table("THA_vol...

...th the command, R CMD INSTALL pls.pcr Installing package `pls.pcr' ... R data help ../TITLE - No such file or directory >>> Building/Updating help pages for package `pls.pcr' Formats: text html latex example pcr.model html latex plot.mvr text html latex example predict.mvr text html latex example sensory text html latex simpls text html latex example summary.mvr text html...

...for (i = 0; i < MIC_MAX_VRINGS; i++) { struct vring_desc *desc; struct vring_avail *avail; @@ -309,38 +308,38 @@ static int mic_vdev_info_show(struct seq_file *s, void *unused) continue; desc = vrh->vring.desc; seq_printf(s, "vring i %d avail_idx %d", - i, mvr->vring.info->avail_idx & (num - 1)); + i, mvr->vring.info->avail_idx & (num - 1)); seq_printf(s, " vring i %d avail_idx %d\n", - i, mvr->vring.info->avail_idx); + i, mvr->vring.info->avail_idx); seq_printf(s, "vrh i %d weak_barri...

Dear list I am using the mvr function of the package pls.pcr to compute PLS resgression using a X matrix of gene expression variables and a Y matrix of medical varaibles. I would like to obtain the R2 (sum of squares captured by the model) and Q2 (proportion of total sum of squares captured in leave-one-out cross validatio...

Dear R-helpers, I have performed a PLS regression with the mvr function from the pls.pcr package an I have 2 questions : 1- do you know if mvr automatically centers the data ? It seems to me that it does so... 2- why in the situation below does the output say that the optimal number of latent variables is 4 ? In my humble opinion, it is 2 because the RMS incr...

I'm trying to get the coefficient of partial determination for each of three independent variables. I've tried mvr in package pls.pcr. I'm a little confused by the output. I'm curious how I can order the LV's according to their names rather than their relative contribution to the regression. For instance, using the crabs data from MASS I made a regression of FL~RW+noise set.seed(124) library(pls.p...

...One simple way to do classification with PLS is to code the classes as 0s and 1s (assuming there are only two classes) or -1s and 1s, fit the model, then threshold the prediction; e.g., those with predicted values < 0.5 (in the 0/1 coding) get labeled as 0s. There's a predict() method for mvr objects, and that's what you need to use to get prediction on test set. There's one more complication: The CV done internal to mvr is optimizing the MSE (because it rightly thinks it has a regression problem), but that will almost certainly not be the thing to do for classification. You...

...", "x5","x6","x7","x8","x9","x10","x11","y1")) attach(quality.data) quality.data # pairs(cbind(x4,x5,y1)) X<-data.frame(x1,x2,x3,x4,x5,x6,x7,x8,x9,x10,x11,y1) Y<-data.frame(y1) quality.simpls<-mvr(X,Y,1:11,method="simpls",validation="CV") #####error happens in this row ,and the error information is about: error in :eval(expr, envir, enclos) :the length of number'envir' is not 1. i don't know how to solve this problem. who can help me make this program corre...

...ames(Data)[4:8] dataset=NULL dataset$X=NULL len=length(variable) for( i in 1:len) { var=variable[i] if(i==1) { dataset$X=as.matrix(Data[var]) } if(i>1) { dataset$X=as.matrix(cbind(dataset$X,Data[var])) } } depVar="Y" dataset$Y=as.matrix(cbind(Data[depVar])) pls1=mvr(Y~X,data=dataset,ncomp=4) summary(pls1) On execution the error is Error in get(as.character(FUN), mode = "function", envir = envir) : object 'X6' of mode 'function' was not found Please help me on this -- View this message in context: http://r.789695.n4.nabble.com/p...

...comps 0.9999 $ R2(testing.plsCV) (Intercept) 1 comps 2 comps 3 comps 4 comps 5 comps 0.0000 0.9678 0.9782 0.9941 0.9991 0.9996 6 comps 0.9997 $ ?crossval "This function performs cross-validation on a model fit by mvr. It can handle models such as plsr(y ~ msc(X), ...) or other models where the predictor variables need to be recalculated for each segment. When recalculation is not needed, the result of crossval(mvr(...)) is identical to mvr(..., CV = TRUE), but slower." If the above result is correct c...

How to use the segments in the PLS fit1 <- mvr(formula=Y~X1+X2+X3+X4+x5+....+x27, data=Dataset, comp=5,segment =7 ) here when i use segments,the error was like this rror in mvrCv(X, Y, ncomp, method = method, scale = sdscale, ...) : argument 7 matches multiple formal arguments Please help -- View this message in context: http://r.7896...

Error in mvr(Kd_nM ~ qsar, ncomp = 6, data = my, validation = "CV", method = "kernelpls") :   Invalid number of components, ncomp How I can fix this? [[alternative HTML version deleted]]

hi R help group, I have installed PLS package in R and use it for princomp & prcomp commands for calculating PCA using its example file(USArrests example). But How I can use PLS for Partial least square, R square, mvrCv one more think how i can import external file in R. When I use plsr, R2, RMSEP it show error could not find function plsr, RMSEP etc. How I can calculate PLS, R2, RMSEP, PCR, MVR using pls package in R. Thanking you........ -- Nitish Kumar Mishra Junior Research Fellow BIC, IMTECH, Chandigarh...

ChangeLog: ========= v2 => v3: a) Patch 1 data structure cleanups, header file include cleanups, IDA interface reuse and switching to device_create_with_groups(..) as per feedback from Greg Kroah-Hartman. b) Patch 7 signal documentation, sleep workaround removal and sysfs access API cleanups as per feedback from Michael S. Tsirkin. v1 => v2: @ http://lwn.net/Articles/563131/ a)

ChangeLog: ========= v2 => v3: a) Patch 1 data structure cleanups, header file include cleanups, IDA interface reuse and switching to device_create_with_groups(..) as per feedback from Greg Kroah-Hartman. b) Patch 7 signal documentation, sleep workaround removal and sysfs access API cleanups as per feedback from Michael S. Tsirkin. v1 => v2: @ http://lwn.net/Articles/563131/ a)

...raction of scores and loadings, and calculation of (R)MSEP and R2 - A simple multiplicative scatter correction (msc) implementation - Functions for plotting predictions, validation statistics, coefficients, scores, loadings, biplots and correlation loadings. The main changes since 1.0-3 are - mvr, mvrCv and predict.mvr now has builtin support for scaling of X. - A new function stdize for explicit centering and/or scaling. - Correlation loadings plot (corrplot). - New argument `varnames' in coefplot, to label the x tick marks with the variable names. - loadingplot, coefplot and plot.mv...