similar to: multiple plot overlay - dataframe

Dear I try to realize one scatter matrix which draws *one single variable to all variables* with *regression line* . You can see my eviews version in the annex . How can I draw this graph with R studio? Sincerely Engin YILMAZ

Dear R User, Please, I am new to R. I want to overlay density plot for predictive interval pooled result in meta-analysis. http://addictedtor.free.fr/graphiques/graphcode.php?graph=114 Regards Frank Peter

Hello, I'm facing a problem of optimization, I've already solved but I'm trying to find other answers to this problem to improve the solution. Well, to make it short: I have to set/install a number of devices in a building, and I have to give service to a number of "customers", or better say, to give a good quality of the signal. The more devices I place, the higher the

How do a plot several columns of a matrix at once in a single plot versus a single x-variable? The default plot.matrix or plot.dataframe commands plot each column versus each other column in several sub-plots. I want to plot each column versus a single other vector (x) as several lines or points in one plot. I can do it by hand: get the range of all variables (i.e. columns of the matrix or

Hello I have a multivariate data frame giving various responses for several treatments. I would like to plot the relationship in the responses in a pairs plot with different symbols for the different treatments. In a regular plot I would have used 'matplot' or just added the new treatments with the 'points' function. But how to do it in a pairs plot? Thank you for your

Hello, all, I have a dataframe of three rows and umpteen columns. I want to show the maximum, minimum, and median with a vertical line and a central dot (I'd use a boxplot, but with only three data points, that's overkill; I can't just use points, because of overlap and some of the other data plotted on the graph). This works: > boxplot(data_frame,

Hi, I have three vectors and I would like to plot them in one window. So R should overlay them in the quartz. I achieved this by plotting the first vector: plot(v1) and add the other two with points(v2) and points(v3). Is there another way to achieve the same result? Cheers -- View this message in context: http://www.nabble.com/Overlay-Plots-tp19918234p19918234.html Sent from the R help mailing

Dear R-users Idea: Plot a dnorm line using specific mean/sd to complete a histogram (skewed). xs:range of y-values, ys: dnorm function Problem: I expected to multiply the ys function with the sample size (n=250-300). I was wondering about a factor between 12'000 and 30'000 to match the size of the dnorm line with the specific histogram. Thanks Sibylle hist(Biotree[Ld,]$Height2008,

Hi, a have some code like myfunc <- function(x) { ...; return c(a,b) } ys <- sapply(0:100,myfunc) so I get something like c(c(a1,b1),c(a2,b2),...) But now I need the "as" and "bs" in one vector as <- apply(ys, function(c(a,b)) a) bs <- apply(ys, function(c(a,b)) b) Can you help me with the correct syntax, instead of my pseudo code? thx Christof

Hello: I'm dealing with an issue currently that I'm not sure the best way to approach. I've got a very large (10G+) dataset that I'm trying to create a histogram for. I don't seem to be able to use hist directly as I can not create an R vector of size greater than 2.2G. I considered condensing the data previous to loading it into R and just plotting the frequencies as a

Here's some code to make lissajous dance. I've attached a small sample GIF. Cheers, Rob Steele robsteele at yahoo dot com plot.lissajous = function(omega.x, omega.y, delta = 0, num.thetas = 200) { thetas = seq(0, 2 * pi, length = num.thetas) xs = sin(omega.x * thetas + delta) ys = cos(omega.y * thetas) plot(xs, ys, type = 'l', lwd = 3, ann = FALSE, axes = FALSE) }

Hello. I am new R user, so this question is probably quite stupid, but for the life of me I cannot figure out how to get predications using multivariate linear regression analysis. Single variable predictions work fine. I am trying the following: -- Known y's for known x's1 and x's2 ys <- c(133890, 135000, 135790, 137300, 138130, 139100, 139900, 141120, 141890, 143230, 144000,

Hi, It is most probably just my R-ignorance, but I have following problem with using predict(). I train the model using 164 cases and then I try to use it on the data set with 35 cases, but I am getting 164 predictions ? R-code below illustrates in more detail what I am doing. Truly yours, R train = read.csv("train.csv", header = TRUE, row.names = "mol",

I am sorry if this is a faq or tutorial somewhere, but I am unable to solve this one. What I am looking for is a count of how many different categories(numbers in this case) that appears for a given factor. Example: > l <- c("Yes", "No", "Perhaps") > x <- factor( sample(l, 10, replace=T), levels=l ) > m <- c(1:5) > y <- factor( sample(m, 10,

If I'm understanding correctly, you're saying that vgather* is slow on all of Excavator, Haswell, Broadwell, and Skylake (client). Therefore, we will not generate it for any of those machines. Even if that's true, we should not define "gatherIsSlow()" as "hasAVX2() && !hasAVX512()". It could break for some hypothetical future processor that manages to

It seems that http://reviews.llvm.org/D15690 only implemented gather/scatter for AVX-512, but not for AVX/AVX2. Is there any plan to enable gather for AVX/2? Thanks. Best, Zhi On Thu, Feb 25, 2016 at 8:28 AM, Sanjay Patel <spatel at rotateright.com> wrote: > I don't think gather has been enabled for AVX2 as of r261875. > Masked load/store were enabled for AVX with: >

I've written a simple function to draw a regression line in a plot and annotate the line showing the slope with a label. It works, as I'm using it, when the horizontal variable is 'x', but gives incorrect results otherwise. What's wrong? # simple function to show the slope of a line show.beta <- function(model, x="x", x1, x2, label, col="black", ...)

Dear R-List users, Can anyone explain exactly the difference between Weights options in lm glm and gls? I try the following codes, but the results are different. > lm1 Call: lm(formula = y ~ x) Coefficients: (Intercept) x 0.1183 7.3075 > lm2 Call: lm(formula = y ~ x, weights = W) Coefficients: (Intercept) x 0.04193 7.30660 > lm3 Call:

Yes, masked load/store/gather/scatter are completed. - Elena From: zhi chen [mailto:zchenhn at gmail.com] Sent: Thursday, February 25, 2016 01:20 To: Demikhovsky, Elena <elena.demikhovsky at intel.com> Cc: Sanjay Patel <spatel at rotateright.com>; Nema, Ashutosh <Ashutosh.Nema at amd.com>; llvm-dev <llvm-dev at lists.llvm.org> Subject: Re: [llvm-dev] how to

That makes great sense. It would be great if we have profitability mode to see the necessity to use gathers. Or it also would be good if there is a compiler option for the users to enable LLVM to generate the gather instructions no matter it is faster or slow. Best, Zhi On Fri, Feb 26, 2016 at 12:49 PM, Sanjay Patel <spatel at rotateright.com> wrote: > If I'm understanding