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...rror: variable 'poly(x, d, raw = T)' was fitted with type "nmatrix.1" but type "nmatrix.10" was supplied Does anyone have any ideas? Thanks, Harold ############################################################################ polyModelSelection <- function(x,y,maxd,add.dim=F) { dim.mult <- 0 if (add.dim) { dim.mult = 1 } bestD <- 1 bestError <- 1 loss <- 1 lm.models <- vector("list",maxd) for (d in 1:maxd) { lm.mod <- lm(y ~ 0 + poly(x,d,raw=T)) lm.models[[d]] <- lm.mod...

...ne help me resolve this? A part of the R function looks like this: print(is.loaded('merge_xtabs_patterns_file')) print(is.loaded('merge_xtabs_patterns_file_')) .Fortran('merge_xtabs_patterns_file_',ydim[1],ydim[2],x=as.integer(as.matrix(y)),na=as.integer(c), maxD=as.integer(maxD),lrowmem=length(rowmem),rowmem=as.integer(rowmem), sequential=as.integer(Sequential),nclust=as.integer(nclust)) The corresponding output: [1] FALSE [1] TRUE Error in .Fortran("merge_xtabs_patterns_file_", ydim[1], ydim[2], x = as.integer(as.matrix(y)), : Fortran s...

...# D: Upper Trianglar Matrix # D[i, j] = Euclidean distance between object i and j (j > i) D[i, j] = max(svd(xa - xb)$d) # the largest singular value } } cat("for (i in 1:(M - 1)) done! \n") maxD = apply(D, 2, max) index_row = apply(D, 2, function(x) which(x == max(x))[1]) dummy = max(maxD) index_column = which(maxD == dummy) m = vector() m[1] = index_row[index_column] m[2] = index_column dminmax[2] = D[m[1], m[2]] for (i in...

...d3D = expand.grid(x = range1D, y = range1D, z = range1D) gridded(grid3D) = ~x+y+z res3D = krige(formula = v ~ 1, data3D, grid3D, model = vgm(1, "Exp", .2)) # convert the result to a data.frame d = as.data.frame(res3D) # compute transparency (proportional to the interpolated value) maxD = max(d$var1.pred) minD = min(d$var1.pred) alpha = (d$var1.pred - minD)/(maxD - minD) # reduce maximum alpha (all points are semi-transparent) alpha = alpha/5 # plot library("rgl") spheres3d(d$x, d$y, d$z, alpha=alpha, radius=0.05) I saw the fog effect but it seems to add a fog...

# Is this a bug or something I don't understand? spline(date, stor, n=52, xmin=mind, xmax=maxd) # gives length(x) of 53 ????, but y has the expected length of 52 # Shouldn't they be the same length? From help (spline): # spline returns a list containing components x and y which give the # ordinates where interpolation took place and the interpolated values # xmin and xmax are inside m...

Hi all, I've got some functioning code that I've literally taken hours to write. My 'R' coding is getting better...it used to take days :) I know I've done a poor job of optimizing the code. In addition, I'm missing an important step and don't know where to put it. So, three questions: 1) I'd like the resulting output to be sorted on distance (ascending) and

...een 0 and 1. The result can be seen at http://sneakymustard.com/tmp/plot.jpg As you can see, the default y axis labels are not very nice, as it uses irregular intervals. I tried using variations of axis(2, at = pretty(c(0, ceiling(max(distances))), 5)) or yaxp = c(round(mind, 2), round(maxd, 2), -4) in the matplot() call. Is there anything else I could try for better labeling of values between 0 and 1 in a log-scale axis? Hints or pointers to the appropriate docs are appreciated :) Also, is there a command/option to change the plotted spacing between the labels in a plot? In the pl...

Linux 3.11 added respective support, so I think we should follow suit. 1: xen: add LZ4 decompression support 2: libxc: add LZ4 decompression support Signed-off-by: Jan Beulich <jbeulich@suse.com>

WARNING: This is not compatible with the previous lz4 patchset. If you''re using experimental compression that isn''t in mainline kernels, be prepared to backup and restore or decompress before upgrading, and have backups in case it eats data (which appears not to be a problem any more, but has been during development). These patches add lz4 and lz4hc compression

...d3D = expand.grid(x = range1D, y = range1D, z = range1D) gridded(grid3D) = ~x+y+z res3D = krige(formula = v ~ 1, data3D, grid3D, model = vgm(1, "Exp", .2)) # convert the result to a data.frame d = as.data.frame(res3D) # compute transparency (proportional to the interpolated value) maxD = max(d$var1.pred) minD = min(d$var1.pred) alpha = (d$var1.pred - minD)/(maxD - minD) # reduce maximum alpha (all points are semi-transparent) alpha = alpha/5 # plot library("rgl") spheres3d(d$x, d$y, d$z, alpha=alpha, radius=0.05) I saw the fog effect but it seems to add a fog...