similar to: how to combine two data frames via factors (or somehow else)

Hi, I am trying to plot two distribution graph on one plot. But I dont know how. I set them to the same x, y limit, even same x, y labels. Code: x1=rnorm(25, mean=0, sd=1) y1=dnorm(x1, mean=0, sd=1) x2=rnorm(25, mean=0, sd=1) y2=dnorm(x2, mean=0, sd=1) plot(x1, y1, type='p', xlim=range(x1,x2), ylim=range(y1, y2), xlab='x', ylab='y') plot(x2, y2, type='p',

Hello R Users, I have vectors x <- c("a2","b7","c8") y1 <- c(1,2,3,2) y2 <- c(4,2,7,5,4,3,8) y3 <- c(1:10) and I want to assign values form vector y1 to a new variable which name comes from the 1st value of the vector x etc. How to do it using only vector x. As a result I should have: a2 <- y1 b7 <- y2 c8 <- y3 More general problem: I have 2 txt

Hi, consider the following two dataframes: x1=c("232","3454","3455","342","13") x2=c("1","1","1","0","0") data1=data.frame(x1,x2) y1=c("232","232","3454","3454","3455","342","13","13","13","13")

Dear R users, I need to compare two scatter plots, plot(x1, y1) plot(x2, y2) and would like to plot them in the same figure. How do I do it? Thank you. -- View this message in context: http://www.nabble.com/two-scatter-plots-in-one-tp21963375p21963375.html Sent from the R help mailing list archive at Nabble.com.

Hi there! Both on windows and Solaris platforms I run into troubles when trying to draw two plots on top of each other. Here a short code example: > x1 <- c(2,3,4,5,6,7,8) > y1 <- sin(x1) > x2 <- c(1,2,3,4,5,6,7,8,9,10) > y2 <- cos(x2) > d1 <- cbind(x1,y1) > d2 <- cbind(x2,y2) > plot(d1) > par(new=T, xaxs="d") > plot(d2) Error in plot.new()

Hello, We would like to begin discussions around a new set of intrinsics, to better express multi-dimensional array indexing within LLVM. The motivations and a possible design are sketched out below. Rendered RFC link here <https://github.com/bollu/llvm-multidim-array-indexing-proposal/blob/master/RFC.md> Raw markdown: # Introducing a new multidimensional array indexing intrinsic ## The

Hi R-experts, suppose I have a list with containing data frame elements: [[1]] (Intercept) y1 y2 y3 y4 -6.64 0.761 0.383 0.775 0.163 [[2]] (Intercept) y2 y3 -3.858 0.854 0.834 Now I want to put them into ONE dataframe like this: (Intercept) y1

> It seems that the main advantage of your proposal is that it would allow for non-constant strides (i.e. variable length arrays) in dimensions other than the first one. Do these appear frequently enough in the programs that you're interested in to be worth optimizing for? Yes - at least in Chapel (which is one of the motivating languages) these are very common. In other words, typical

Dear WizaRds, Working through sampling theory, I tried to comprehend the concept of stratification and apply it with Survey to a small example. My question is more of theoretic nature, so I apologize if this does not fully fit this board's intention, but I have come to a complete stop in my efforts and need an expert to help me along. Please help: age<-matrix(c(rep(1,5), rep(2,3),

We could also simply extend the existing inrange mechanism to non-constantexpr GEPs.  It would remove an inconsistency in the semantics, be relatively straight forward, and solve the motivating example. (I didn't read the proposal in full, so there may be other examples it doesn't solve.) Philip On 7/22/19 10:01 AM, Peter Collingbourne via llvm-dev wrote: > The restrictions of

Dear R experts, Wish you all a HAPPY NEW YEAR! How do I go about plotting (using lattice) overlays of an ID (group=ID) observed, fitted data in each panel of a multiple panel plot (each panel identified by DS1 + DS2 + DS3)? "x" variable is X1 in the accompanying section of a dataset. each individual is identified by color and Y's are identified by "pch" or "lty".

Dear mailing list, I have following array: X2 Y2 [1,] 422.7900 6.0 [2,] 469.8007 10.5 [3,] 483.9428 11.0 [4,] 532.4917 25.5 [5,] 596.1942 33.5 [6,] 630.8496 40.5 [7,] 733.2996 45.0 [8,] 946.4779 32.0 [9,] 996.8068 35.5 [10,] 1074.3310 23.0 I do afterwards the following: plot.new() plot.window(xlim=c(min(X1)-50,max(X1)+50),

Hi, I have a data.frame with columns named X, D1, D2, D3 I know I can get a single plot with 3 curves by doing xyplot(D1 + D2 + D3 ~ X, data) but in some cases I might have columns D1 ... D10. Is there a way to plot all 10 columns without having to specify each individual term? (By analogy with formulae in lm, I thought, xyplot(. ~ X, data) would work, but it didn't) Thanks, --

It's also very common in Fortran. -David Michael Ferguson via llvm-dev <llvm-dev at lists.llvm.org> writes: >> It seems that the main advantage of your proposal is that it would >> allow for non-constant strides (i.e. variable length arrays) in >> dimensions other than the first one. Do these appear frequently >> enough in the programs

I'm new in both R and statistics. I "did my homework", I tried the archives and whatever I managed to get from the sources, but still I need assistance with the plsr package. I have a model with 2 core determinants D1 and D2, made by 3 indicators each (D1a,D1b,D1c and so on). Also I have 2 moderating variables (m1,m2), where m1 moderates D1 and m2 modarates D2. The dependent

hey, folks, I have two very simple questions. I am not quite sure if I can do this using R. so, I am analyzing a large data frame with thousands of variables. For example: Dependent variables: d1, d2, d3 (i.e., there are three dependent variables) Independent variables: s1, s2, s3, ......s1000 (i.e., there are 1000 independent variables) now I want to run simple linear regression analyses of

Hi, I have got four correlation matrix. They are the same set of variables under different conditions. Is there a way to test whether the correlation matrix are significently different among each other? Could anyone give me some advice? -- View this message in context: http://www.nabble.com/correlation-matrix-difference-tf4073868.html#a11578046 Sent from the R help mailing list archive at

Hi, I have a data set with two continous variables that I want to plot MEANS (I am not intrerested in median values) on a double-y graph. I also have 2 factors. I want the factor combinations plotted in different panes. Dummy dataset: mydata <- data.frame(factor1 = factor(rep(LETTERS[1:3], each = 40)), factor2 = factor(rep(c(1:4), each = 10)), y1 =

Dear R users, If I have to combine plots which have the same independent and dependent variables in one graph. Which command should I use? Any example? Can I use "panel"? Your help will be deeply appreciated. Thanks! -Vivien Chen- [[alternative HTML version deleted]]

hello all I am writing a quite simple script to study dental wear patterns in humans and I wrote this function sqrt(var(Y1)+var(Y2))^2-4(var(Y1)*(var(Y2)-cov(Y1,Y2)^2)) but appear this error message Error: attempt to apply non-function alternatively I wrote this sqrt(var(Y1)+var(Y2)^2)-4[(var(Y1)*(var(Y2)-cov(Y1,Y2)^2))] but this error message appear [1] NA Warning message: NAs introduced