search for: xprime

...s/percentiles within R while also using a weighting schema, I would be very interested. Note - this function supposes the data in X is time-sequenced, with the most recent (and thus heaviest weighted) data at the end of the vector WtPercentile <- function(X=rnorm(100), pctile=seq(.1,1,.1)) { Xprime <- NA for(i in 1:length(X)) { Xprime <- c(Xprime, rep(X[i], times=i)) } print("Percentiles:") print(quantile(X, pctile)) print("Weighted:") print(Xprime) print("Weighted Percentiles:") print(quantile(Xprime, pctile, na.rm=TRUE)) } WtPerce...

...aa bb a 1 "A" b 2 "B" The advantage of this is that I could access all the individual components easily. Also I could access all the rows and columns easily. Alternatively, I could have a list of lists that looks like this: xprime <- list() xprime$a <- list() xprime$b <- list() xprime$a$aa <- 1 xprime$a$bb <- "A" xprime$b$aa <- 2 xprime$b$bb <- "B" etc. If speed is important, would a list of lists be faster than a data frame? (I know, for example, that scan is supposed to be faste...

...ation correlation matrix sigma sigma<-matrix(0,p,p) #creates a px p matrix of 0 rank<-2 for (i in 1:rank){ for (j in 1:rank){ rho<-0.75 sigma[i,j]<-rho^abs(i-j) sigma[i,i]<-1 } } # create a data set of 10 observations from multivariate normalcovariance matrix sigma library(MASS) Xprime<-mvrnorm(N,rep(1,p), sigma ) Also, if I calculate S<- cov(Xprime) will S be the sample correlation matrix? Thank you very much for your time!

...ollowing; the system consists of s species, i= 1, 2,...,s network of interactions between species is specified by a (s x s) real matrix, C[i,j] x[i] being the relative population of the "ith" species (0 =< x[i] =< 1, sum(x[i]=1) the evolution rule being considered is as follows; xprime[i] = f[i] if x[i] > 0 or f[i] >= 0 xprime[i] = 0 if x[i] = 0 and f[i] < 0 where f[i] = sum(C[i,j]*x[j]) - x[i]*sum(C[k,j]*x[j]) I have a bit of attempted code written out, but are there any tricks or tips that would condense or make this mess look nicer? -Justin

G'day, All. I have been trying to trackdown a problem in my R analysis script. I perform a scale() operation on a matrix then do further work. Is there any way of inverting the scale() such that sX <- scale(X) Xprime <- inv.scale(x); # does inv.scale exist? resulting in Xprime_{ij} == X_{ij} where Xprime_{ij} \in R There must be some way of doing it but I'm such a newb that I haven't been able to find it. Thanks Godfrey

...Here is a sample code; library(mva) set.seed(12345) x <- as.matrix(dist(matrix(rnorm(100),ncol=10,byrow=T))) # x[1,2]<-x[2,1]<-1000 ## <<--** 1 # x[5,6]<-x[6,5]<-1000 ## <<--** 2 fit <- NULL for(k in 1:9) { mds <- cmdscale(x,k,add=T) xprime <- as.matrix(dist(mds$points)) fit[k] <- sum((x-xprime)^2)/sum(x^2) } plot(fit) When I run this example, it gives a nice "good" plot. However, with those two commented lines added, the plot is opposite, that is, the fit is increasing as k grows! I really don't und...

Hi, I am using plot to show scatter points in 2_D. in my data, there is no data between -1 and +1 in x-axis. I want to skip this region, i.e. x axis becomes [-Inf:-1, 1:Inf]. can any one tell me how to do? YU [[alternative HTML version deleted]]

Dear all, I am new to plotting Taylor Diagram using plotrix package within R, hence this post. I have written a script which plots Taylor Diagram with one reference and 7 model values. However the font size, line width and line type are not clear when saving the diagram as a jpeg file. I tried the functions lty, lwd and font but no apparent change. I am attaching the script here. Any help would