similar to: DierckxSpline segfault

Dear "R" users, I have a question about the Package DierckxSpline. I have tried to find the answer by myself but it didn't worked out. I wondered if Dierckxspline can use different sets of y values in one time to fit a line with knot. I have different sets of Y values representing the same thing for different voxels (in an fmri image). I have already fitted the data in different

Suppose I have two variables, x and y. For a fixed number of knots, I want to create a spline transformation of x such that a loss function is minimized. Presumably, this loss function would be least squares, i.e. sum (f(x)-y)^2. The spline transformations would be linear, quadratic or cubic. I know I can solve this problem using some optimization function in R, but I was wondering if anyone

I like what smooth.spline does but I am unclear on the output. I can see from the documentation that there are fit.coef but I am unclear what those coeficients are applied to.With spline I understand the "noraml" coefficients applied to a cubic polynomial. But these coefficients I am not sure how to interpret. If I had a description of the algorithm maybe I could figure it out but as it

Hi, All: How do I get information about the "R CMD check / build / install" process, especially regarding what software to install and how to configure it under Windows XP? I ask, because "R CMD check" complained, "gfortran: Command not found". I found 'gfortran-sjlj.exe' in 'C:\Program Files\R\Rtools\MinGW\bin', which is in the

Hello: Under my Windows 7 system, "R CMD check DiercxkSpline_1.1-5.tar.gz" fails because: f951.exe: sorry, unimplemented: 64-bit mode not compiled in make: *** [bispev.o] Error 1 gfortran -m64 -O2 -mtune=core2 -c bispev.f -o bispev.o f951.exe: sorry, unimplemented: 64-bit mode not compiled in make: *** [bispev.o] Error 1 ERROR: compilation failed for package

I've written a series of functions that evaluates an integral from -inf to a or b to +inf using equally spaced quadrature points along a normal distribution from -10 to +10 moving in increments of .01. These functions are working and give very good approximations, but I think they are computationally wasteful as I am evaluating the function at *many* points. Instead, I would prefer to use

Hi, I am looking for an R package that would calculate multivarite (mostly 2d and 3d, tensor) cubic interpolating splines, so that I could evaluate these splines (and their derivatives) at many points (unkown at the time of calculating the spline polynomials) repeatedly. To make things concrete, I have an array V with dim(V) = k and gridpoint vectors grid=list(...), length(grid[[i]])==k[i],

Shown below is most of the FORTRAN subroutine named HCLUST. My question concerns the DO loop labeled as '10'. What happened to its CONTINUE statement? I will assume that after FLAG(I)=.TRUE. is executed that control returns to DO 10 I=1,N. Am I correct? Dave ---------------------------- C Initializations C DO 10 I=1,N C We do not initialize MEMBR in order to be able to

I would like to get some idea of which R-packages are popular, and what R is used for in general. Are there any statistics available on which R packages are downloaded often, or is there something like a package-survey? Something similar to http://popcon.debian.org/ maybe? Any tips are welcome! ----- Jeroen Ooms * Dept. of Methodology and Statistics * Utrecht University Visit

On Solaris, the environment variable MAIL gets set to /var/mail//user, (with double // before user name),which breaks some MUAs, e.g. emacs' Rmail. The problem lies in the fact that /usr/include/maillock.h has: #define MAILDIR "/var/mail/" while session.c adds another / snprintf(buf, sizeof buf, "%.200s/%.50s", _PATH_MAILDIR, pw->pw_name); This only

iommufd follows the same design as KVM and uses memory cgroups to limit the amount of kernel memory a iommufd file descriptor can pin down. The various internal data structures already use GFP_KERNEL_ACCOUNT to charge its own memory. However, one of the biggest consumers of kernel memory is the IOPTEs stored under the iommu_domain and these allocations are not tracked. This series is the first

iommufd follows the same design as KVM and uses memory cgroups to limit the amount of kernel memory a iommufd file descriptor can pin down. The various internal data structures already use GFP_KERNEL_ACCOUNT to charge its own memory. However, one of the biggest consumers of kernel memory is the IOPTEs stored under the iommu_domain and these allocations are not tracked. This series is the first

iommufd follows the same design as KVM and uses memory cgroups to limit the amount of kernel memory a iommufd file descriptor can pin down. The various internal data structures already use GFP_KERNEL_ACCOUNT to charge its own memory. However, one of the biggest consumers of kernel memory is the IOPTEs stored under the iommu_domain and these allocations are not tracked. This series is the first

iommufd follows the same design as KVM and uses memory cgroups to limit the amount of kernel memory a iommufd file descriptor can pin down. The various internal data structures already use GFP_KERNEL_ACCOUNT to charge its own memory. However, one of the biggest consumers of kernel memory is the IOPTEs stored under the iommu_domain and these allocations are not tracked. This series is the first

iommufd follows the same design as KVM and uses memory cgroups to limit the amount of kernel memory a iommufd file descriptor can pin down. The various internal data structures already use GFP_KERNEL_ACCOUNT to charge its own memory. However, one of the biggest consumers of kernel memory is the IOPTEs stored under the iommu_domain and these allocations are not tracked. This series is the first

iommufd follows the same design as KVM and uses memory cgroups to limit the amount of kernel memory a iommufd file descriptor can pin down. The various internal data structures already use GFP_KERNEL_ACCOUNT to charge its own memory. However, one of the biggest consumers of kernel memory is the IOPTEs stored under the iommu_domain and these allocations are not tracked. This series is the first

Change the sg_alloc_table_from_pages() allocation that was hardwired to GFP_KERNEL to use the gfp parameter like the other allocations in this function. Auditing says this is never called from an atomic context, so it is safe as is, but reads wrong. Signed-off-by: Jason Gunthorpe <jgg at nvidia.com> --- drivers/iommu/dma-iommu.c | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff

Change the sg_alloc_table_from_pages() allocation that was hardwired to GFP_KERNEL to use the gfp parameter like the other allocations in this function. Auditing says this is never called from an atomic context, so it is safe as is, but reads wrong. Signed-off-by: Jason Gunthorpe <jgg at nvidia.com> --- drivers/iommu/dma-iommu.c | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff

This patch adds the ia64-specific code for new Qemu . In addition, some ia64 patches aren''t checked into xen-unstable.hg, so I reversed the related logic temporarily. Once sync with xen-ia64-unstable.hg, the logic will regain automatically. Thanks & Best Regards -Xiantao OTC,Intel Corporation _______________________________________________ Xen-devel mailing list