similar to: predicting with stl() decomposition

Dear all: In what I am doing I sometimes get a (Hessian) matrix that has a couple of tiny negative eigenvalues (e.g. -6 * 10^-17). So, I can't run a Cholesky decomp on it - but I need to. Is there an established way to regularize my (Hessian) matrix (e.g., via some transformation) that would allow me to get a semi-positive definite matrix to be used in Cholesky decomp? Or should I try some

Thanks for all the helpful responses. I include the data file and the syntax file for reference. Again, if I use the fields function, as is, I get the message: Error in svd(tempM) : error 159 in dsvdc using traceback, I get: > traceback() 4: stop(paste("error ", z$info, " in dsvdc")) 3: svd(tempM) 2: Krig(x, Y, cov.function = rad.cov, m = m, decomp = decomp,

Thank you so much David, here is correction: d1=suppressWarnings(read.csv("/Users/anamaria/Downloads/B1.csv", stringsAsFactors=FALSE, header=TRUE)) d1$X <- NULL d2=as.matrix(sapply(d1, as.numeric)) pdf("~/graph.pdf") b<-barplot(d2, legend= c("SYCL", "CUDA"), beside= TRUE,las=2,cex.axis=0.7,cex.names=0.7,ylim=c(0,80), col=c("#9e9ac8",

Hello, I have a data frame like this: d11=suppressWarnings(read.csv("/Users/anamaria/Downloads/B1.csv", stringsAsFactors=FALSE, header=TRUE)) > d11 X Domain.decomp. DD.com..load Neighbor.search Launch.PP.GPU.ops. Comm..coord. 1 SYCL 2. 1 0 3.7 0. 1 1 .6 2 CUDA 2 0 3. 1 0 1 .0

I have a recurring graphics issue that I've not been able to resolve with R. If I make a series of regression estimates and then plot the estimated function for the regression lines over a scatter plot of the data, e.g., using a sequence of plot( ) and lines ( ) similar to those below

Hi All. I've run into a problem with the plinear algorithm in nls that is confusing me. Assume the following reaction time data over 15 trials for a single unit. Trials are coded from 0-14 so that the intercept represents reaction time in the first trial. trl RT 0 1132.0 1 630.5 2 1371.5 3 704.0 4 488.5 5 575.5 6 613.0 7 824.5 8 509.0 9

I have been struggling to find some informaation on what lm exactly does. I know it uses the QR decomp. However, I was recently faced with a somewhat badly scaled matrix and summary(lm) said Coefficients: ( 4 not defined because of singularities) does anyone know how lm chooses these 4 coef. is it forward building of the model --> drop last when qr sends a non full rank design matrix? My

Dear R contributors, Considering the following sample C code, that illustrates two possible uses of a Cholesky decomp for inverting a matrix, equally valid at least in theory: SEXP test() { int d = 2; int info = 0; double mat[4] = {2.5, 0.4, 0.4, 1.7}; double id[4] = {1.0, 0.0, 0.0, 1.0}; double lmat[3]; F77_CALL(dpotrf)("L", &d, mat, &d, &info); lmat[0] = mat[0]; lmat[1]

Dear all: Could anyone please provide some R codes to plot the below survival data to compare two groups (0 vs 1) after 2 simulations (TRL)? need 95% prediction interval on the plot from these 2 trials. I would like to simulate 1000 trials later. Thanks a lot for your great help and consideration! yan TRL ID ECOG BASE PTR8 GROUP POP ST ind 1 1 1 1 2.2636717 0.255634126 1 1 99.4 F 3 1 2 1

Given four known and fixed vectors, x1,x2,x3,x4, I am trying to generate a fifth vector,z, with specified known and fixed partial correlations. How can I do this? In the past I have used the following (thanks to Greg Snow) to generate a fifth vector based on zero order correlations---however I'd like to modify it so that it can generate a fifth vector with specific partial

Dear R gurus I am running a GLMM that looks at whether chimpanzees spend time in shade more than sun (response variable 'y': used cbind() on counts in the sun and shade) based on the time of day (Time) and the availability of shade (Tertile). I've included some random factors too which are the chimpanzee in question (Individual) and where they are in a given area (Zone). There are

I was wondering if there's any non-executable stack patch for FreeBSD's kernel. I searched in google but all I got was some questions in freebsd-security back from 2001 and an answer saying someone heard about a project like this, but no information at all. Is there any patch like PaX or Openwall available for FreeBSD? I dont want to discuss if its useless or not since there're a

From: Sebastian Andrzej Siewior <sebastian at breakpoint.cc> The "zstd at breakpoint.cc" compression algorithm enables ZSTD based compression as defined in RFC8478. The compression is delayed until the server sends the SSH_MSG_USERAUTH_SUCCESS which is the same time as with the "zlib at openssh.com" method. Signed-off-by: Sebastian Andrzej Siewior <sebastian at

Is there any way to give a "decent" title after I plot something generated by decompose? For example: # generate something with period 12 x <- rnorm(600) + sin(2 * pi * (1:600) / 12) # transform to a monthy time series y <- ts(x, frequency=12, start=c(1950,1)) # decompose z <- decompose(y) # plot plot(z) Now, the title is the ugly "Decomposition of additive time

I need to perform a QR-decomposition of a sparse matrix, so I've been trying to use the Matrix package. Unfortunately I don't seem to be getting exactly the same results as if I had used the qr() command from the base package. Here is an example of what I'm doing. > spdata <-rpois(50,1) > y <- rnorm(10,0,1) > S <-

Hi, I have a data frame like this: > dput(df) structure(list(ID = 1:8, Type = c("gmx mdrun -ntmpi 8 -ntomp 1 -s benchPEP.tpr -nsteps 10000 -resethway", "gmx mdrun -ntmpi 8 -ntomp 1 -s benchPEP.tpr -nsteps 10000 -resethway", "gmx mdrun -ntmpi 8 -s benchPEP.tpr -nsteps 4000 -resetstep 3000", "gmx mdrun -ntmpi 8 -s benchPEP.tpr -nsteps 4000 -resetstep

I am experiencing some odd behavior with the .Call interface, and I am hoping someone out there can help me with it. Below is a simple example (in that there are R packages that do exactly what I want), but this code illustrates the problem. Thanks in advance for any help you can provide. Suppose I want to compute the log density of a multivariate normal distribution using C code and the gsl

Dear all, I have a problem similar to what was already posted about two years ago (http://tolstoy.newcastle.edu.au/R/help/05/01/10011.html): I have a binary file, which contains a header and data compressed by zlib and written to the file as unsigned character. Here is, what I try to do: > zz <- file(in.file, 'rb') > ## the header has to be read in three parts due to the

On 25/11/14 22:05, Andy Ritger wrote: > On Tue, Nov 25, 2014 at 10:57:44AM -0500, Ilia Mirkin wrote: >> On Mon, Nov 24, 2014 at 8:33 PM, Andy Ritger <aritger at nvidia.com> wrote: >>> On Fri, Nov 21, 2014 at 01:39:55AM -0500, Ilia Mirkin wrote: >>>> On Fri, Nov 21, 2014 at 1:16 AM, Andy Ritger <aritger at nvidia.com> wrote: >>>>> Hi Ilia,

Hi, I asked this question before, which was hidden in a bunch of questions. I repharse it here and hope I can get some help this time: I have 2 contingency tables which have the same group variable Y. I want to compare the strength of association between X1/Y and X2/Y. I am not sure if comparing p-values IS the way even though the probability of seeing such "weird" observation under H0