similar to: error on Fast bilinear interpolator from a grid

Dear all, there are R packages able to simulate or estimate bilinear model for time series? I know it is an open problem, but do exist something for very simplified bilinear models? Alternatively, what kinfd of non linear time series models are performed in R? If R is not able, could someone suggest me for some commercial softwares to deal with bilinear models? i'm afraid of a negative

I think this is an easy question, but I would be grateful for any advice on how to implement this in R. I simply have a response variable (y) that I am trying to predict with one explanatory variable (x) but the shape of the scatter plot is distinctly bilinear. It would be best described by two straight lines. Is there a way of fitting a linear model to give me a bilinear fit and (more

Dear all, I'm having trouble interpolating a number of gridded datasets that I have. I'm quite new to R so any help/advice that can be offered would be much appreciated! Firstly I'll describe my dataset. The data is a grid of the planet at 1 degree spatial resolution, with each grid cell containing a value describing a particular variable (e.g. population density) for coordinate

Hello R help I have been trying to use Rob Hyndman's monotonically increasing spline function. But like another user or two seem have a problem with a missing DLL (namely "spline_coef"). None of the previous help postings seemed to have any solutions to this problem. As per a Ripley suggestion I have deleted all previous versions of R and reinstalled R 2.7.0 and the problem

Hi, I'd like to compare SST data for year 2000 with SST for year 2001. I managed to get filled contour plots showing monthly SST for both years (12 plots for each year, 24 plots in total). In order to compare year 2000 and year 2001, however, I'd need to have the same legend scale (same color bar) in both years plots. Thus, my question is: is there a way to set the legend scale in

Hi useR's I have created a simple map of the world using the following code: m <- map(xlim=c(-180,180), ylim=c(-90,90)) map.axes() I then create a grid of dimension 36x72 using the code: map.grid(m, nx=72, ny=36, labels=FALSE, col="black") This gives 2592 grid cells. In a separate data set of dimension 36x72, I have 2592 temperature values (some missing values are present)

Hi, I have plot a graphics by next way: par(mar=c(5,5,1,1), font.axis=3, ps=14, xaxs="i", yaxs="i", lab=c(18,18,7), font .lab=3); plot(l, b, type="n", xlim=c(0,360), ylim=c(-90,90), xlab="l, deg", ylab="b, deg"); points(l, b, cex=vel/60, col=1, pch=21); On this plot I have axis x (denoted by l) ranged in [0,360] with labeling step 20. But I

Am just feeling my way into the grid library, and cannot figure out how to define the plot limits. 3/5 of the example polygons below plot in the default 0-1 range viewport. But when I try to redefine the viewport the polygons plot in the same places. I also get the same result without employing push/pop. (As you can see from the scale I'm trying to introduce, I want to plot map polygons.)

I am using following codes to plot map library(sp) library(rgdal) library(maps) library(gplots) library(clim.pact) library(fields) source("/R/PlotGridded2DMap.R") source("/R/image.plot.fix.R") source("/R/image.plot.plt.fix.r") seasonal_plot<-function(input,lonll=-180,latll=-90,lonres=5.,latres=3.75,write_file=TRUE,The_title=NULL){ if(is.null(The_title)){

Hi, My general goal is to find a coding strategy to efficiently store and retrieve drawing routines for different plots. This is my approach so far. In a single text file I store multiple drawing routines where each routine draws a different plot. A drawing routine may look like this: panel.mean <- function(means,...){ dots <- list(...)

I've just spent today trying to fix a Heisenbug... this function returns a linear interpolator function: interpOne <- function(xl,yl){ f = function(data){ t = (data-min(xl))/(max(xl)-min(xl)) return(min(yl)+t*(max(yl)-min(yl))) } return(f) } > k=interpOne(c(0,1),c(4,5)) > k(0.5) [1] 4.5 and this function uses the above to return a function that returns a piece-wise

Theora-devs: I am in seek of a theora (but possibly vorbis/ogg/ffmpeg) dev to optimize the encoding in a realtime software product. We do live encoding and transcode into ogg/theora/vorbis at various resolutions and frame rates. The higher resolutions cannot process in realtime and we are pushing the boundaries of hardware (cpu) encoding with the existing theora/ffmpeg. Right now we have to

Hi everybody I need help to solve the following problem in finite element A field variable f(x,y)=x? y is defined over a rectangle domain ?={K: 0?x?4 , 0?y?6? Given the expression g=?_(0 0)^(6 4)??X^3 Y dx dy? And assume the following bilinear interpolation shape functions are used to discretize the spatial geometric variable x and y: N1= ? (1-z)(1-e) N1= ? (1+z)(1-e) N1= ? (1+z)(1+e) N1=

> -----Original Message----- > From: r-help-bounces at stat.math.ethz.ch > [mailto:r-help-bounces at stat.math.ethz.ch]On Behalf Of Mike J Smith > Sent: 09 June 2005 09:58 > To: r-help at stat.math.ethz.ch > Subject: [R] krig.image help > > > Hi > > I have recently been experimenting with the use of kriging, primarily > through Goldensoftware's Surfer.

Dear all, This problem came up initially while debugging a function, but it seems to be a more general problem of R. I hope I'm wrong, but I can't find another explanation. Let me illustrate with the raster package. For an object "RasterLayer" (which inherits from Raster), there is a method xyValues defined with the signature

May I ask why you're doing 512x512 instead of 1024x1024? These are already scaled up coordinates, so 1024x1024 should work no? Or is it because of the seams on the edges? Do those not also appear with 512x512 or does it sample outside of the box? Separately, why not use this approach on nv40 as well? I can't imagine the blitter would be faster... does this result in lower quality? On

We do not have a generic blitter on nv3x cards, so we must use the sifm object for color resolving. This commit divides the sources and dest surfaces in to tiles which match the constraints of the sifm object, so that color resolving will work properly on nv3x cards. Signed-off-by: Hans de Goede <hdegoede at redhat.com> --- Changes in v2: -Use 1024x1024 blocks -Use the sifm on both nv3x

I''ve tried migrating acts_as_attachment to attachment_fu (just to see if I could replace RMagick with ImageScience+FreeImage), but the quality of the thumbnails is just horrendous, blurred beyond recognition (downscaling a 1280x1024 to a few considerably smaller thumbnails). Changing attachment_fu to use RMagick again and the thumbnails were crispy sharp again. I was wondering

I wanted a simple function for bilinear interpolation on a 2-D grid, and interp.surface() in the fields package didn't quite suit my needs. In particular, it requires uniform spacing between grid points. It also didn't have the "visual" reference frame I was looking for. Here is an alternative function, followed by an example. # A function for bilinear interpolation on a 2-d

I understand that the capture/playback signals need to be sync'd for an AEC to adapt. I'm a little bit confused on the requirements of synchronous sampling between the near end (mic/speaker) and the far end (phone line). I have an embedded DSP system with mic and speaker getting 1msec packets containing 8 samples. We can watch the DSP and ISDN clock frames drift and every few minutes we