similar to: To make a graph for 4 functions

Hi All, We have a raw dataset that, on the sampling time column, for example: t <- c(0,1,2,5,0,5,0,2,5) And we need to create a second column that indicates the day of the sampling, so the end result of what we want is a vector: 1,1,1,1,2,2,3,3,3 Additional information that might simplify the matter is that, for each day, the time starts with zero and ends with 5. I am a beginner with R.? So

Full_Name: Michael Hoffman Version: 2.1.0 OS: Linux (Fedora Core 3, kernel 2.6.11-1.14_FC3) Submission from: (NULL) (193.62.199.8) help(arrows) says: """ arrows(x0, y0, x1, y1, length = 0.25, angle = 30, code = 2, col = par("fg"), lty = NULL, lwd = par("lwd"), xpd = NULL) ... If 'code=2' an arrowhead is drawn at

Hello dear members of R-help and R-core mailing list, I am not sure if this request is a "ticket" that should be filled somewhere outside the mailing list. If so, I apologize for not doing and would like to know where I should have filled it. And to the subject matter: I would like to use a command like this: plot(c(1,8), 1:2, type="n") polygon(1:7, c(2,1,2,NA,2,1,2),

Hello dear members of R-help and R-core mailing list, I am not sure if this request is a "ticket" that should be filled somewhere outside the mailing list. If so, I apologize for not doing and would like to know where I should have filled it. And to the subject matter: I would like to use a command like this: plot(c(1,8), 1:2, type="n") polygon(1:7, c(2,1,2,NA,2,1,2),

Dear R-users, I am facing problem with integrating in R a likelihood function which is a function of four parameters. It's giving me the result at the end but taking more than half an hour to run. I'm wondering is there any other efficient way deal with. The following is my code. I am ready to provide any other description of my function if you need to move forward.

Hi. Maybe this is a stupid question. If so, I apologize, but here goes. Suppose I have a function f1(x,...) that calls a function f2(y1,y2,...,yn) in the following way: if x satisfies a certain condition, then I want to call f2(x,y2,...,yn); otherwise I want to use the default value of y1, if there is one. I could do something like the following: v <- ifelse ( is.null(x), f2( , y2,...,

Dear all, I would like to draw a dendrogram and mark some parts/branches (by using "segments") including their labels. If I draw it without specifying the length of x axix, I am able to do that (as in My dendrogram 1 of the following codes). However, if I want to specify the x axix, I am not able to draw marking line (by using "segments") including labels (as in My dendrogram

Hi, I have a small dataset that I'm fitting a segmented regression using nls on. I get a step below minimum factor error, which I presume is because residual sum of square is still "not small enough" when steps in the parameter space is already below specified/default value. However, when I look at the trace, the convergence seems to have been reached. I initially thought I might

library(nlme) data(Phenobarb) na.include <- function(x)x phe1 <- nlme(conc~phenoModel(Subject, time, dose, lCl, lV), data = Phenobarb, fixed = lCl+lV~1, random= pdDiag(lCl+lV~1), start = c(-5,0), na.action = na.include, naPattern = ~!is.na(conc)) phe.ranef <- ranef(phe1,augFrame=TRUE) plot(phe.ranef, form=lCl~Wt+ApgarInd) [Error in max(length(x0),

Using the PPC frsqrte and fres instructions, I got the percentage time take in the smoothing code in _vp_compute_mask() down from 13.64% to 1.88% of the running time. In my local copy of Vorbis I have a fast_math.[hc] in vorbis/lib and have a _fast_sqrt() inline in fast_math.h. If anyone else wants to try it out, it follows. I can currently encode my test file (the first 15 seconds of

Hi R experts, I'm trying to use nls() for a piecewise linear regression with the first slope constrained to 0. There are 10 data points and when it does converge the second slope is almost always over estimated for some reason. I have many sets of these 10-point datasets that I need to do. The following segment of code is an example, and sorry for the overly precise numbers, they are just

I suggest a simple enhancement to segments() and arrows() to facilitate drawing horizontal and vertical segments -- set default values for the second x and y arguments equal to the first set. This is handy, especially when the expressions for coordinates are long. Compare: Segments: < function (x0, y0, x1 = x0, y1 = y0, col = par("fg"), lty = par("lty"), --- > function

I was teaching new R users to make some fun graphs. I had some arrows examples worked up we came across a problem. The arrows function ignores 2nd and following elements of vectors given as code an angle. Would you please consider 1) allowing vectors for code and angle, or 2) returning an error or warning when user mistakenly supplies a vector for those parameters? When code like this is

There was an inquiry on this list recently about plotting some simple error bars on a graph. Now Splus has a function (error.bar --- originally written by Sue Clancy of DMS, CSIRO, I believe) to do this job virtually at the touch of a key. (Well a few keys. :-) ) The error.bar function is written completely in raw S --- no calls to ``.Internal'' or anything like that. So it would be

Hi, Yes, I can see why that would not work. The sinking algorithm in SimplifyCFG isn't particularly clever. In particular it can't reason about memory ordering and aliasing. In unswitch1(), it can identify that the stores correlate because the correlating stores appear in the same relative source order. In unswitch2() they have been permuted, and the algorithm cannot deal with this. This

Uwe Ligges suggested I post this on R-bugs as a wishlist item with a proposed patch. R considers zero-length arguments to segments() to be an error. I would like R to allow this and to return without an error. It occurs naturally in settings like valid <- c(FALSE, FALSE, FALSE) segments(x0[valid], y0[valid], x1[valid], y1[valid]) For what it may be worth, S-Plus does not consider

Thanks, Looks like inst combine do the job On Tue, Apr 25, 2017 at 9:36 PM, Davide Italiano <davide at freebsd.org> wrote: > On Tue, Apr 25, 2017 at 9:24 PM, Hongbin Zheng via llvm-dev > <llvm-dev at lists.llvm.org> wrote: > > Hi, > > > > Is there a pass in LLVM that can optimize: > > > > if (x) > > a[i] = y0; > > else > >

arrows() seems to hang when either x or y scale of the plot is logarithmic and the arrows requested go beyond the plot (by more than a certain amount). I didn't go into C code to find it, but here's a function that exercises the bug a bit ... arrow.bug2 <- function(y0=1,y1=10,log="y") { plot(c(0.1,1),c(1,10),log=log) arrows(x0=0.5, y0=y0, x1=0.5,

Hello, I've made a backend for Tile64 processor as my master's thesis. Of course, there is a lot to do in order to harness all the power of the processor, but LLVM programs already can be compiled to tile assembly. If anyone interested in the backend, just let me know and I release the code on our project site. One way to improve my backend is to utilize its ILP capabilities, so I'd

In the fir_mem_up filter, the inner loop does a mac on the y0, y1, y2, y3 variables. What is the range of values of those variables? I would like to move the SHR 1 outside the loop after the mac has been done. Will this result in a 32 bit overflow of the y0, y2, y2 and y3 variables? -Fritz On2 Technologies, Inc. http://www.on2.com