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Hai From which CRAN mirror can get the package ‘LPP2005REC’ Ram [[alternative HTML version deleted]]

Dear R users, I'm interested in a combination of a scatterplot and an image graph. I have two large vectors. Because in the scatterplot some areas are sparsely and others densely populated, I want to see the points, and I also want their color to be changed based on their density (similar to a heat map). Is there a function that can do that? Thank you, b.

Hi, Anybody know what are the common Standard statistical methods used for the analysis of a dataset,and anybody know which of these methods give similar results Ram [[alternative HTML version deleted]]

Hi, I'm using the densCols function for a scatterplot and cannot figure out 1) how to extract the computed densities, and 2) how to create a legend based that represents the upper and lower ranges of the densities. For example: movers.den <- densCols(move$x, move$y) table(movers.den) #08306B #083775 #083B7C #083D7E #3989C1 #3F8FC4 28 22 101 25

Hi all, I have been looking for means of add a contour around some points in a scatterplot as a means of representing the center of density for of the data. I'm imagining something like a 95% confidence estimate drawn around the data. So far I have found some code for drawing polygons around the data. These look nice, but in some cases the polygons are strongly influenced by outlying points.

 Dear Madame or Sir,I am having a problem in combining density-smoothed scatterplot matrices with a plot of kernel destiny estimations of each dimension plotted on the respective field of the diagonal.I have tried following approach using the package "sm" for the kernel density estimation, as well as "MASS" respectively:pairs(myTable[, 1:4],panel=function(x,y, ...){

Dear R Community, I recently read an article and found a plot as attached. It has scatterplot, barplot, and error bar. Could anyone help me to figure out what package I can use in R to generate such plot? Thank you very much for any inputs! Kind regards, Ace -------------- next part -------------- A non-text attachment was scrubbed... Name: Screen Shot 2018-02-04 at 6.38.14 AM.png Type: image/png

Hai i just wanted to know how we can find the package of a dataset, eg: how can i find the package in which the dataset *iris* is present Ram [[alternative HTML version deleted]]

Hi all, This is probably going to come off as unnecessary (and show my ignorance) but I am trying to understand the parameter estimates I am getting from R when doing an ANCOVA. Basically, I am accustomed to the estimate for the categorical variable being equivalent to the respective cell means minus the grand mean. I know is the case in JMP - all other estimates from these data match the

Dear R-list, I have made a simple kernel density estimation by x <- c(2,1,3,2,3,0,4,5,10,11,12,11,10) kde <- density(x,n=100) Now I would like to know the estimated probability that a new observation falls into the interval 0<x<3. How can I integrate over the corresponding interval? In several R-packages for kernel density estimation I did not found a corresponding function. I

Hello R users & R friends, I just want to ask you if density() can produce a confidence interval, indicating how "certain" the density() line follows the true frequency distribution based on the sample you feed into density(). I've heard of loess.predict(loess(y ~ x), se=TRUE) which gives you a SE estimate of the smoothed scatterplot - but density() kernel smoothing is not the

Hi all We are pretty new to R here and trying to achieve something that we believe is possible but it?s not easy to work out how to do it. We are producing scatterplot matrices for e.g. 10 variables. What we would like to do is superimpose 2D kernel density estimators on top of each plot so that we end up with a scatterplot matrix of 2D kernel density (contour) plots. The kernel density plots

Hi Ace, You can do it with plotrix: library(plotrix) barpos<-barp(c(1,5,38),width=0.5,col=c("white","lightgray","darkgray"),ylim=c(0,70)) ehplot(c(1,0.8,0.9,0.8,1.1,1,4,3,5,14,3,2,32,27,33,30,50,61), c(1,1,1,1,1,1,2,2,2,2,2,2,3,3,3,3,3,3),median=FALSE,add=TRUE,cex=2, pch=21,bg="white") dispersion(barpos$x,barpos$y,c(0.1,1,5),lwd=2,arrow.cap=0.03)

Installing packages from binaries on Windows seems broken, when using mirrors that are up to date with CRAN install.packages( 'httr', type = 'binary', repos = "https://cran.rstudio.com/" ) Changing repos to the Kansas CRAN mirror installs the package as expected, but that could be because the KS mirror has not yet synced. Someone pointed out that the PACKAGES.gz

Thanks to David and Jorge - both of your helpful suggestions got me to the desired endpoint. In case anyone else has this question: I boxplotted my y variable data, but did the "cut" operation on the x variable in order to conserve the order of the y data. I see another suggestion coming in from another user that basically says this. So, my working line of code was: boxplot(count$RPKM

How can perform logarithmic binning in the scatterplot? I could only take the log of the variables and plot them, but I am sure that is not the way. I have a very huge data, and would want to plot those high density scatterplots and code then with different colors for the bins/density. -- View this message in context:

I am getting an error message from scatterplot: > library(car) > scatterplot(Prestige$income~Prestige$type) Error in Summary.factor(c(2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, : range not meaningful for factors In addition: Warning message: In Ops.factor(x[floor(d)], x[ceiling(d)]) : + not meaningful for factors > The command does output the kind of graph that I want (boxplots).

Hello R folks, I am encountering a problem with the following scatterplot function from the car package: > scatterplot(y~x|z) where y and x are continuous (interval) random variables and z is a categorical variable. When z is a categorical variable coded 1 or 2, I (appropriately) get a scatterplot of y by x, coded by z. Similarly, when z is a categorical variable coded 1, 2, or 3, there is

Dear all, I created a bivariate normal distribution: set.seed(138813) n<-100 x<-rnorm(n); y<-rnorm(n) and plotted a scatterplot of it: plot(x,y) Now I'd like to add the 2D-standard deviation. I found a thread regarding plotting arbitrary confidence boundaries from Pascal H?nggi http://www.mail-archive.com/r-help at r-project.org/msg24013.html which cites the even older thread

If I make a scatterplot and several (e.g. 5) points lie on top of each other at a given x,y location I would like the plot symbol to be the number of superimposed points (e.g. "5"). Could someone please tell me how to do this in R? Thanks! Bill Simpson