search for: eqscplot

I found the following in eqscplot, library MASS: When given just one point, it fails: > eqscplot(x=1, y=1) Error in plot.window(xlim, ylim, log, asp, ...) : need finite xlim values After inserting browser() just before the last line in eqscplot() (in which plot() gets called), I found the following: > eqscplot(x=1, y...

...one can scale the plot axes equally when no indication has been given of the scaling expected for either! It has always seemd to be that plot(x=1, y=1) shoul dnot work: it has not supplied enough information! On Thu, 8 Nov 2001 pflugshaupt@geobot.umnw.ethz.ch wrote: > I found the following in eqscplot, library MASS: > > > When given just one point, it fails: > > > eqscplot(x=1, y=1) > Error in plot.window(xlim, ylim, log, asp, ...) : > need finite xlim values > > After inserting browser() just before the last line in eqscplot() (in which > plot() gets called)...

Dear all I was writing some code that needed functions from packages 'MASS' and 'CircStats', and I received a warning saying that the function 'eqscplot' in one of the packages was masked by another 'eqscplot' from the other package (in fact 'eqscplot' from 'CircStats' seems a short version of 'eqscplot' from 'MASS'). This masking of functions may become a serious problem as the number of packages in CRAN...

...o be happy with it. ============================ library(MASS) library(stats) data(iris3) ir<-rbind(iris3[,,1],iris3[,,2],iris3[,,3]) ir.species<-factor(c(rep("s",50),rep("c",50),rep("v",50))) ir.lda<-lda(log(ir),ir.species) ir.ld<-predict(ir.lda,dimen=2)$x eqscplot(ir.ld, type="n", xlab = "First linear discriminant", ylab = "second linear discriminant") text(ir.ld, labels= as.character(ir.species[-143]), col =3 +codes(ir.species),cex =0.8) ====================================== eqscplot does not plot anything and it gives me...

...ov.rob(x, method="mcd") center <- cr$center # calculate squared euclidean and mahalanobis d <- rowSums(t(t(x)-center)^2) m <- as.vector(mahalanobis(x, center, cr$cov)) # euclidean an dmahalanobis basically coincide, mahalanobis slightly biased by robust covariance underestimation eqscplot(x=d, y=m); abline(0,1) # Now I add a highly redundant column in hope the distances between cases will not change x2 <- cbind(x, x[,1]+rnorm(n, sd=0.01)) # scale, otherwise euclidean fails x2 <- scale(x2) cr2 <- cov.rob(x2, method="mcd") center2 <- cr2$center d2 <- rowSums...

...figure out what seems to be a very simple problem (and is still taking me hours...). I want to draw a simple scatterplot but with 'equal' axes, i.e. I want both axes to go from -3 to 3. Values for x lie between -2 and 0.5, values for y between -2.2 and 3. I have tried 'usr' and 'eqscplot' and a few other options, but it doesn't give me the desired result. Many thanks!!! Ellen

...igures work OK when I plot to the screen, but when I try to do the same plot as a postscript file, I get an unexplicable error, > figframe() Error in if (yuin > xuin * ratio) yuin <- xuin * ratio else xuin <- yuin/ratio : missing value where TRUE/FALSE needed > traceback() 2: eqscplot(x = 0, y = 0, xlim = xlim, ylim = ylim, xlab = xlab, ylab = ylab, type = "n") 1: figframe() > Here is a minimal source script exhibiting the problem: library(MASS) eps <- function(file="Rplot.eps", horizontal=FALSE, paper="special", ...) { postsc...

...applied the lda function on a small dataset of mine. Any help will be much appreciated. > library(MASS) > AA<-read.table("http://www.natursyn.dk/online/fingerprinting.txt",header=T) > aa.lda<-lda(as.matrix[3:9],AA$group) > aa.ld<-predict(aa.lda,dimen=2)$x > eqscplot(aa.ld,type="n",xlab="LD1", ylab="LD2",las=1) > text(aa.ld,c(rep('f',13),rep('b',10),rep('p',10))) > aa.mean<-lda(aa.ld,AA$group)$means > points(aa.mean,pch=3) Best, Thomas Larsen Leibniz-Laboratory for Stable Isotope Research M...

Dear useRs, I'd like to produce some scatter plots where N units on the X axis are equal to N units on the Y axis (as measured with a ruler, on screen or paper). This approach x <- sample(10:200,40) ; y <- sample(20:100,40) windows(width=max(x),height=max(y)) plot(x,y) is better than plot(x,y) but doesn't solve the problem because of the other parameters (margins etc). Is

...re(MASS) dat <- gamSim(1,n=200,dist="normal",scale=2) summary(b <- gam(y~s(x0)+s(x1)+s(x2)+s(x3),data=dat)) summary(a <- lm(y~x0 + x1 + x2 + x3,data=dat)) se.result <- data.frame(linear.se=predict(a, se.fit=TRUE)$se.fit, gam.se=predict(b, se.fit=TRUE)$se.fit) with(se.result, eqscplot(linear.se, gam.se)) abline(a=0, b=1) -- This message (and any attachments) is for the recipient ...{{dropped:8}}

Greetings, I am working on a stylometric analysis of some latin texts; one of the latest stylometric techniques involves using principal components analysis. Not being a statistician, I can't really fully rely on PCA as my primary tool, since I don't really understand the statistics behind the PCA technique. Nevertheless, the ability to use PCA and graph the results has been

Last week I asked about data ellipses with rgl:::ellipse3d() with lines showing the principal axes. (The goal is a visual demonstration of PCA as a rotation of variable space to component space.) I was trying, unsuccessfully, to use princomp() to generate the PCA axes and plot them using segments3d: > > PC <- princomp(trees) > > sdev <- PC$sdev # component standard

Hi, I have a question about computing shortest Euclidean distances between two data frames of spatial points... I have 2 dataframes (not yet converted to spatial class) >Sewers<-data.frame(x=c(10,20,35,50),y=c(100,150,200,300)) >transect <- data.frame(x=seq(from=0, to=50, by=1),y=seq(from=100, to=150, by=1)) I would like to be able to compute the shortest distance from the

Hello: What I want to do is quite simple, but I can't find a way. I have a data frame with several points (x and y coords). I want to add another column with cluster membership. For example aggregate all the points that stand within a distance of 40 from each other. I've tried using "nncluster" from the package nnclust, but the results are not correct, for some

I want to plot something (eg a circle) with a fixed ratio of the x and y axis, or (even better) with a fixed size when I print it. Output should then be a circle (actually it'll be someting more complicated) with radius 5cm and not an ellipse. I'm _sure_ this is not new, but after looking 45min for a solution, I post here... Thanks for help Thomas

Greetings. I'm about to embark on my first big (to me at least!) R project, which will be to write a function to plot three-dimensional multiple correspondence analysis (mca) plots in a manner similar to scatterplot3d(). (plot.mca() plots only two dimensions, even though mca() will calculate more.) Before I do so, however, I would love to know that I'm not reinventing the wheel or any

Hi, I was wondering if anyone knows of a way by which one can estimate values from a contour plot created by using the loess function? I am hoping to use the loess contour plot as a means of interpolation to identify the loess created values at points at pre-defined (x,y) locations. Could anyone point me in the right direction please? Thanks. Laura Quinn Institute of Atmospheric Science School

Hello everybody, I am doing a plot and I would like to know which parameter I have to use in order to get an equal scale for the axes x and y: Means, if the intervals in the x-axis is 0,5,10,15.... I would like to have the same scale for the y-axis. Thank you so much for your help. Halima from Leiden where the sun is shining. Holland

....debian.org/r/r-cran-mass.html which is the same day when r-base was released for R 3.4.0, so MASS was obviously built against the current version. I just tried r-cran-spatial on a **fresh Debian sid chroot**, and get > library(spatial) > example(surf.gls) srf.gl> library(MASS) # for eqscplot srf.gl> data(topo, package="MASS") srf.gl> topo.kr <- surf.gls(2, expcov, topo, d=0.7) Error in surf.gls(2, expcov, topo, d = 0.7) : object 'VR_frset' not found so it seems to me this must affect all packages in Debian sid that were built before the release of R 3.4.0...

Suppose I have the following data I want to scatterplot: > xy [,1] [,2] [1,] 0 0 [2,] 21 4 I start up a graphics window and fire away: > plot(xy) - but because the graphics window is square, the aspect ratio is wrong. So I add: > plot(xy, asp=1) - now the aspect ratio is correct, but the Y range is about -8 to 11, whereas my data has a Y range of 0