search for: yright

...d onto present/absent p-values (y) between 0 and 1 using the *approxfun - function*{stats}; when I have used R version 2.8, everything had worked fine, however, after updating to R 2.11.1., I got unexpected output (explained below). Please correct me here, but as far as I understand, the yleft and yright arguments set the extreme values of the interpolated y-values in case the input x-values (on whose approxfun is applied) fall outside range(x). So if I run approxfun with yleft=1 and yright=0 with y-values between 0 and 1, then I should never get any values higher than 1. However, this is not the c...

...precheza.cz> Sent: 23 November 2017 16:22:39 To: Eliza Botto; r-help at r-project.org Subject: RE: adding percentage secondary y-axis Hi It is usually not recommended but if you insist maybe library(plotrix) ?twoord.plot twoord.plot(lx=D[,1],ly=D[,2], rx=D[,1], ry=D[,3]) or plot.yy(x=D[,1],yright=D[,3], yleft=D[,2]) which allows only one x axis (see below). Cheers Petr plot.yy <- function (x, yright, yleft, yleftlim = NULL, yrightlim = NULL, xlab = NULL, yylab = list(NA, NA), pch = c(1, 2), col = c(1,2), linky = F, smooth = 0, lwds = 1, length = 10, format = "%d/%...

Hi It is usually not recommended but if you insist maybe library(plotrix) ?twoord.plot twoord.plot(lx=D[,1],ly=D[,2], rx=D[,1], ry=D[,3]) or plot.yy(x=D[,1],yright=D[,3], yleft=D[,2]) which allows only one x axis (see below). Cheers Petr plot.yy <- function (x, yright, yleft, yleftlim = NULL, yrightlim = NULL, xlab = NULL, yylab = list(NA, NA), pch = c(1, 2), col = c(1,2), linky = F, smooth = 0, lwds = 1, length = 10, format = "%d/%...

Dear useRs, I have this dataset (D) with three columns. > dput(D) structure(c(1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 2.990484802, 3.005018792, 3.019552781, 3.03408677, 3.048620759, 3.063154749, 3.077688738, 3.092222727, 3.106756717, 3.121290706, 3.135824695, 3.150358684, 3.164892674, 3.179426663, 3.193960652, 3.208494642, 3.223028631, 3.23756262,

...said: > I am not really a R specialist but for this task I use function: and he pasted his code into the email. I reindented the code, and wrote a fragment to experiment with it. Here it is: --------------------------------------------------------------------------- plot.yy <- function(x, yright, yleft, yleftlim=NULL, yrightlim = NULL, xlab = NULL, yylab=c("",""), pch=c(1,2), col=c(1,2), linky=F, smooth=0, lwds=1, length=10, format="%d-%H:%M", ......

...above code. With asp not set, R plays close attention to the value of ylim. This is not intuitive behaviour, or is it? How can I set the aspect ratio, and simultaneously set the plot region? The aspect ratio is one number and the plot region is given by four numbers (xleft, xright, yleft, yright). Logically, these 5 numbers are independent of each other and arbitrary, provided xleft<xright and yleft<yright. This should give a one-to-one bijection between 5-tuples and plots, determined up to a change of scale that is uniform in the x- and y-dirctions. My code above shows the...

Dear R-devel, The following line crashes R > approx(1, 1, 0, method='const', rule=2, f=0, yleft=NULL, ties='ordered')$y Process R:2 exited abnormally with code 5 at Tue Jul 21 14:18:09 2009 > version _ platform i386-pc-mingw32 arch i386 os mingw32 system i386, mingw32 status major 2 minor 9.1 year

How do I plot using multiple(2) y-axes? I have two series that use the same x-data, but have very different scales. Appreciate any feedback, Per Bak

hi all i have another probably simple question. I have three variables say x, y and z. x and y are quite large and z is relative small. how can one plot the three variables on the same graph with two separate axis? (one for x and y and the other for z) e.g. x<-c(101,110,150,167,120) y<-c(120,135,175,95,200) z<-c(0.001, 0.15, 0.6, 0.8, 1) regards Allan

Hi to all, First of all, I prefer to tell that I am a R-newbie, so I apologize if this is a silly question (I have tried looking in the manuals, but without luck). I have two variables, y and z, that I want to plot against x in the same plot. I have done this before, using points() after plot(). But now the problem is that y and z are in different units of measurement, and their ranges are very

Hi All, I have checked everything I could find abot graphics, but still cannot solve the problem. Are there any ways to make a graph that plots two lines and two different y-axes, each of them has a scale that is related to the respective line. For example, y1 has a range 1:50 and y1 ranges 0:1. The x-axe is the same for both. Thank you in advance. --- Gregor Gawron

...;=k[2]] z<-z[z>=k[1]] n <- length(x) if (n < 1) stop("'x' must have 1 or more non-missing values") vals <- unique(z) rval <- approxfun(vals, cumsum(tabulate(match(x, vals)))/n, method = "constant", yleft = 0.1, yright = 0.9, f = 0, ties = "ordered") class(rval) <- c("ecdf", "stepfun", class(rval)) attr(rval, "call") <- sys.call() rval }** (I also tried it with yleft = 0, yright = 1, it gave the same error) But appearently it is wrong and it gives the...

...he package redo the creation of function f1. The value of approxfun is a function; for example, I have > f1 function (v) .C("R_approx", as.double(x), as.double(y), as.integer(n), xout = as.double(v), as.integer(length(v)), as.integer(method), as.double(yleft), as.double(yright), as.double(f), NAOK = TRUE, PACKAGE = "base") $xout <environment: 0x17719324> I don't really understand how this is stored, and in particular, how I should handle it so as to include the function f1 in a package. I would like the users to be able to load the package and u...

...nt(knots(Fn12), dig=2) 12*Fn12(knots(Fn12)) ## ~= 1:12 if there were no ties summary(Fn12) summary.stepfun(Fn12) print(ls.Fn12 <- ls(env= environment(Fn12))) ##[1] "f" "method" "n" "x" "y" "yleft" "yright" ############# Example by ?ecdf My objetive seems to this: plot(Fn12) identify( x = knots(Fn12), y = ??????????, labels="my string set") or text... thanks in advanced klebyn

...fficial R FAQ or docs. I have simply something like this: > f<-approxfun(data[,1],data[,2]) and f is: > f function (v) .C("R_approx", as.double(x), as.double(y), as.integer(n), xout = as.double(v), as.integer(length(v)), as.integer(method), as.double(yleft), as.double(yright), as.double(f), NAOK = TRUE, PACKAGE = "base")$xout <environment: 02106C24> I also used "locPoly". Both yield either a function or a data frame of values. Is there a way to get a mathematical representation of the function, e.g. a polynomial of any order? Something like...

Full_Name: Martin Frith Version: R-2.0.0 OS: linux-gnu Submission from: (NULL) (134.160.83.73) I have large vectors containing 100,000 to 20,000,000 numbers. However, they only contain a few hundred *distinct* numbers (e.g. positive integers < 200). When I do ecdf(v), it either runs out of memory, or it succeeds, but when I plot the ecdf with postscript, the output is unnecessarily bloated

...;- sort(x) n <- length(x) if (n < 1) stop("'x' must have 1 or more non-missing values") vals <- sort(unique(x)) rval <- approxfun(vals, cumsum(tabulate(match(x, vals)))/n, method = "constant", yleft = 0, yright = 1, f = 0, ties = "ordered") class(rval) <- c("ecdf", "stepfun", class(rval)) attr(rval, "call") <- sys.call() rval --- [/R-code] --- I think one of the two calls to sort can be removed, improving the performance. What do you...

...80 6 9 90 9 10 100 NA > testinterpolationvalues<-approxfun(testinterpolation,y=NULL) > testinterpolationvalues function (v) .C(C_R_approxfun, as.double(x), as.double(y), as.integer(n), xout = as.double(v), as.integer(length(v)), as.integer(method), as.double(yleft), as.double(yright), as.double(f), NAOK = TRUE, PACKAGE = "stats")$xout <bytecode: 0x33ffab84> <environment: 0x34072eac> > testinterpolationvalues<-approx(testinterpolation,y=NULL) > testinterpolationvalues $x [1] 10.00000 11.63265 13.26531 14.89796 16.53061 18.16327 19.79592 21.42...

Hi, Suppose I have two vectors, not necessarily the same length (in fact, they usually are different lengths): y.1 that has increasing values between 0 and 1; y.2 that has decreasing values between 1.0 and 0. You can picture these as being supply (= y.1) and demand (= y.2) curves from economics. I typically plot these vectors on the same graph against a common x variable, which happens to

Dear All, My doubt about how to integrate a simple kernel density estimation goes on. I have seen the recent posts on integrate density estimation, which seem similar to my question. However, I haven't found a solution. I have made two simple kernel density estimation by: kde.1 <-density(x, bw=sd(x), kernel="gaussian")$y # x<- c(2,3,5,12) kde.2 <-density(y,