similar to: extension to plot.formula?

Thanks to Andy Liaw and Baz for alternatives to tinkering with plot.formula to get plot(cbind(y1,y2) ~ x, ...) to work. However... > From: "Liaw, Andy" <andy_liaw at merck.com> matplot(x, cbind(y1, y2), ...) > From: Barry Rowlingson <B.Rowlingson at lancaster.ac.uk> xyplot(y1+y2~x,data=xyy,allow.multiple=T) The former requires separate code for the

Dear all, While showing some commands of R to my students, I came across the following behaviour of * which surprised me. > set.seed(20) # to make it reproducible # create some objects > z <- matrix(rnorm(6), ncol=2) # 3x2 matrix > x1 <- rnorm(3) # vector of length 3 > y1 <- rnorm(4) #

##data y1 <- matrix(c(3,1,0,1,0,1,1,0,0,0,1,0,0,0,1,1,0,1,1,1), nrow = 5, byrow = TRUE) y2 <- matrix(c (3,0,10,3,3,0,0,1,1,0,0,0,0,0,1,0,1,0,0,2,1,0,1,1,0,2,1,1,4,1), nrow = 5, byrow = TRUE) y1 <- as.data.frame(y1) y2 <- as.data.frame(y2) rownames(y1) <- rownames(y2) <- paste("site", 1:5, sep = "") colnames(y1) <-

Dear Berwin, Simply stacking the problems and treating the resulting observations as independent will give you the correct coefficients, but incorrect coefficient variances and artificially zero covariances. The approach that I suggested originally -- testing a linear hypothesis using the coefficient estimates and covariances from the multivariate linear model -- seems simple enough. For

Suppose I have two sets of (x,y) points like this: x1<-runif(n=10) y1<-runif(n=10) A<-cbind(x1,y1) x2<-runif(n=10) y2<-runif(n=10) B<-cbind(x2,y2) I would like to measure how similar the two sets of points are. Something like a correlation coefficient, where 0 means the two patterns are unrelated, and 1 means they are identical. And in addition I'd like to be able to

Dear all, I'm looking to create a formula within a function to pass to glmer() and I'm having a problem that the following example will illustrate: library(lme4) y1 = rnorm(10) x1 = data.frame(x11=rnorm(10), x12=rnorm(10), x13=rnorm(10)) x1 = data.matrix(x1) w1 = data.frame(w11=sample(1:3,10, replace=TRUE), w12=sample(1:3,10, replace=TRUE), w13=sample(1:3,10, replace=TRUE)) test1 <-

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

Hi, I have measured two response variables (y1, y2) at each treatment level (x = 0, 1.5 or 3). Now I would like to show the y1 and y2 against x in a bar plot. However, y1 and y2 differ in scale so I need two y-axises, one on the left side and one on the right side (and I dont want to standardize my responses). This is fairly easy if you want to show points,lines etc, but gets more complicated

Hi R, y1 <- zoo(matrix(1:10, ncol = 2), 1:5) colnames(y1)=c("a","b") y2 <- zoo(matrix(rnorm(10), ncol = 2), 6:10) colnames(y2)=c("b","a") > y1 a b 1 1 6 2 2 7 3 3 8 4 4 9 5 5 10 > y2 b a 6 0.9070204 0.3527630 7 1.2405943 0.8275001 8 -0.1690653 -0.1724976 9 -0.6905223 -1.1127670 10

Hi all, I'm extracting the name of the term in a regression model that dropterm specifies as the least significant one, and I'm assigning this name to an object. However, when I use update(), it ignores this object. Is there a way I can make it not ignore it? A reproducible example is below: > lm(x1~1+y1*y2+y3+y4,data=anscombe)->my.lm >

gReetings, I want to manipulate a formula object, containing the name "." so that "." is replaced by a desired (arbitrary) expression. What is a safe way to do this? Adrian Baddeley

Although this should be trivial, I'm having a spot of trouble. I want to make a lattice plot of the format y1+y2 ~ x | grp but then fit a lm to each y variable and add an abline of those models in different colors. If the xyplot followed y~x|grp I would write a panel function as below, but I'm unsure of how to do that with y1 and y2 without reshaping the data before hand. Thoughts

Hi R lovers I would like to know how to step to the next line in the R console editor without breaking the continuity of my code more clearly : if for example I write a function, so far i have to write the all code inside on the same line wich may become obscure as the function is more and more complex. I would like to do like in the example of the manuels: >twosam <- function(y1, y2) {

Hi - I'm up against a complicated reshape problem. I have data of the form X1,Y1,hr1,hr2,hr3 X1,Y2,hr1,hr2,hr3 X1,Y3,hr1,hr2,hr3 X2,Y1,hr1,hr2,hr3 X2,Y2,hr1,hr2,hr3 X2,Y3,hr1,hr2,hr3 where X and Y are factors and the hr(1,2,3) are values. I need it as ,X1, X2 Y1,hr1,hr1 Y1,hr2,hr2 Y1,hr3,hr3 Y2,hr1,hr1 Y2,hr2,hr2 Y2,hr3,hr3 .., Any hints? I've been at it for hours. p -- View

Dear all I have a code like x<-1:10 y1<-x+runif(10)*2 y2<-seq(0,50,length.out=10)+rnorm(10)*10 par(mfrow=c(1,2)) plot(y1~x) plot(y2~x) Now I would like to plot y1 and y2 on the same graph, with its two scales (y1 on left and y2 on rigth side). Any help are welcome. Kind regards Miltinho Brazil [[alternative HTML version deleted]]

Hi all, Using xyplot I want to print to Y variables (y1, y2) versus X, conditional on the group. How can I obtain a line (type="l") for one relationship (ie. y1 ~ x) and points (type="p") for the other (y2 ~ x) ? library(lattice) # create some sample data df<-data.frame(group=as.factor(c(rep("a",4), rep("b",4))), # grouping variable for conditional

Dear R users, I have two n*1 integer vectors, y1 and y2, where n is very very large. I'd like to compute elbp = 4^(y1) * 5^(y2) * sum_{i=0}^{max(y1, y2)} [{ (y1-i)! * (i)! * (y2-i)! }^(-1)]; that is, I need to compute "elbp" for each (y1, y2) pair. So I made R code like below, but I don't think it's efficient Would you plz tell me how to avoid this "for"

Hi, I was wondering why the results from lm and dynlm are not the same for what I think is the same model. I have just modified example 4.2 from the Pfaff book, please see below for the code and results. Can anyone tell my what I am doing wrongly? Many thanks, Werner set.seed(123456) e1 <- rnorm(100) e2 <- rnorm(100) y1 <- ts(cumsum(e1)) y2 <- ts(0.6*y1 + e2) lr.reg <- lm(y2

Dear List, I am trying to find each time a value changes in a dataset. The numbers are variables for day vs. night values, so what I am really getting is the daily sunrise and sunset. A simplified example is the following: x<-seq(1:100) y1<-rep(1,10) y2<-rep(2,10) y<-c(y1,y2,y1,y1,y1,y2,y1,y2,y1,y2) xy<-cbind(x,y) I would like to know each time the numbers change. Correct

Dear All, I would be very appreciative of your help with the following 1). I am running multivariate multiple regression through the manova() function (kindly suggested by Professor Venables) and getting two different answers for test=c("Wilks","Roy","Pillai") and tests=c("Wilks","Roy",'"Pillai") as shown below. In the