similar to: Efficient method: Equality of all elements of two vectors

Hello, suppose I have a multivariate multiple regression model such as the following: > DF<-data.frame(x1=rep(c(0,1),each=50),x2=rep(c(0,1),50)) > tmp<-rnorm(100) > DF$y1<-tmp+DF$x1*.5+DF$x2*.3+rnorm(100,0,.5) > DF$y2<-tmp+DF$x1*.5+DF$x2*.7+rnorm(100,0,.5) > x.mlm<-lm(cbind(y1,y2)~x1+x2,data=DF) > coef(x.mlm) y1 y2 (Intercept)

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"

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

Hi, Suppose I already have two plots on the same screen, and I want to draw lines in each of them. Is that possible in R? It seems that once you have two plots on the screen, you can only draw lines in the the last plot, never the 1st. Here is what I mean: #some data y1=rnorm(1:3) y2=rnorm(1:3) #draw two plots on the same screen par(mfrow=c(2,1),oma = c(6, 0, 5, 0)) par(mar=c(0, 5.1, 0, 5.1))

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',

Is there a simpler way then the solution to the one that was posted here? I'm not very proficient with legend, and I don't understand this solution. All I have is two or more lines on one plot that I want to put a legend on and I can't figure out how to do it from the examples. Can you give a very simple example? It does not have to be fancy!! I have never worked with a

Hi, I want to use the value of variable to quote elements in matrix. For example, I have a matrix like:               y1   y2m1         1      2m2         3      4 where y1,y2,m1,m2 are column and row names.  I have two random character variable, say x,  that could be either  y1 or y2  and  y that could be either m1 or m2.  So can I  do like   Matrix[y,x] to quote elements?  I've tried this

Hi, I have a vector Y1 <-c(8, 11, 7, 5, 6, 3, 6, 3, 3) and an index iy <-c(c(1, 2),c(1 2), c(1, 2, 3, 4), c(2, 3, 5), c(4), c(5, 6, 7), c(7, 8, 9)) how can I produce the mean, or the sum of the elements specified in the index iy from the vector Y1? expecting something like this for the sum: Y2 19 19 31 24 5 15 12 I thought lapply function may perform this, but does not work:

Hi, Please can you tell me what I am doing wrong. When trying to merge two xts objects, one of which has multiple character vectors for columns...I am just getting NAs. > str(t) POSIXct[1:1], format: "2011-01-04 11:45:37" > y2 = xts(matrix(c(letters[1:10]),5), order.by=as.POSIXct(c(t + 1:5))) > names(y2) = c(1,2) > y2 1 2 2011-01-04 11:45:38

Hello! I have a set of data of the form (x, y1, y2) where x is the independent variable and (y1, y2) is the response pair. The model is some messy non-linear function: (y1, y2) = f(x; param1, param2, ..., paramk) + (y1error, y2error) where the parameters param1, ..., paramk are to be estimated, and I'll assume the errors to be normal for sake of simplicity. If there were only one

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

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

Hello. I have a 4 dimensional array and I want to fill in the slots with values which are a function of the inputs. Through searching the forums here I found that the function "outer" is helpful for 2x2 matrices but cannot be applied to general multidimensional arrays. Is there anything which can achieve, more efficiently than the following code, the job I want? K <-

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 >

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, 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

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

Dear R-users,  I have a problem, I have the following dataframe:   d<-data.frame(  'y1'=c(1,2,1,2,1,NA,NA), 'y2'=c(1,2,1,1,1,2,1), 'y3'=c(1,NA,1,NA,NA,2,1), 'y4'=c(NA,2,NA,1,1,2,NA), 'a'=c(1,1,1,1,1,1,2) ) where the last variable counts the number of missing values in a row. Now, i want to set rows where a>1 to NA and arrive at something like the

hello, I want to simulate 200 times the mean of a joint probability (y1) and 200 times the mean of another joint distribution (y2), that is I'm expecting to get 200 means of y1 and 200 means of y2. y1 and y2 are probabilities that I calculate from the marginal prob. (z1 and z2 respectively) multiple by the conditional prob. (x1 and x2 respectively), which I generaterd from the binomial

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