similar to: R newbie question

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, I am plotting values of log(hazards ratio) as a function of two predictors, using the plotting function filled.contour(). Here is a simple simulated example of this: x <- seq(0,1, length=20) y <- seq(0,1, length=20) z <- outer(x,y, function(x,y) x^2 + y^2 ) zmat <- matrix( rexp(n=400, rate = z+0.001), 20, 20) filled.contour(x, y, log(zmat),

Hi All I have been fitting regression models and would now like to produce some contour & image plots from the predictors. Is there an easy way to do this? My current (newbie) experience with R would suggest there is but that it's not always easy to find it! f3 <- lm( fc ~ poly( speed, 2 ) + poly( torque, 2 ) + poly( sonl, 2 ) + poly( p_rail, 2 ) + poly( pil_sep, 2 ) + poly( maf, 2

Hello I'm trying to calculate 2d confindence bounds into a scatterplot using the function "kde2d" (package MASS) and a contour plot. I found a similar post providing a solution - unfortunatly I do not realy understand which data I have to use to calculated the named "quantile": Post URL: http://tolstoy.newcastle.edu.au/R/help/03b/5384.html > (...) > >> 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

Hi, Please see the attached contour plot (I am sorry about the big file). This was created using the vis.gam() function in "mgcv" package. However, my question is somewhat broader. In generating this figure, I first created the contours using vis.gam() and then I plotted the points. These point are plotted on top of the contours so that some of the contour lines are only partially

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 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.

Note: I have posted this on SO also but while the question has been upvoted, there has been no answer yet. https://stackoverflow.com/questions/46622243/ggplot-plot-2d-probability-density-function-on-top-of-points-on-ggplot Apologies for those who have seen it there also but I thought that this list of experts may have someone who knows the answer. I have the following example code:

Hello R experts I am looking for: - advice - sample commands - pointers in MASS 4E - packages That help to produce 1D and 2D response plots from quadratic RSM linear regression models that have been produced in R. Let me explain a little what I mean. For 1D plots I mean the variable range (either scaled or actual) on the X axis and the Y axis showing the model prediction (preferably with

Hi, I am no expert on ggplot2 and I do not know the answer to your question. I looked around a bit but could not find an answer right away. But one possibility could be, if a direct approach is not possible, to draw ellipses corresponding to the confidence regions of the multivariate t density and use geom_polygon to draw this successively? I will wait for a couple of days to see if there is a

Hi BFD, ?geom_contour() *does* have helpful examples. Your Google-foo is weak: Searching for geom_contour brought me: http://ggplot2.tidyverse.org/reference/geom_contour.html as the first result. HTH Ulrik On Mon, 9 Oct 2017 at 08:04 Big Floppy Dog <bigfloppydog at gmail.com> wrote: > Can someone please point me to an example with geom_contour() that uses a > function? The help

Can someone please point me to an example with geom_contour() that uses a function? The help does not have an example of a function, and also I did not find anything from online searches. TIA, BFD ----------------------------------------------------------------------------------------------- How about geom_contour()? Am So., 8. Okt. 2017, 20:52 schrieb Ranjan Maitra <maitra at

Some of you may recall that a few months ago I solicited advice and opinions on both R-help and R-sig-teaching about an "introduction to R" workshop I intended to present to a class of high school students enrolled in a 3-year longitudinal science research class. Much lively discussion ensued. Well, I did the workshop on 8 November, and thought I'd give some follow-up as to how it

Dear all, I have a very simple question about how I can include HPD confidence lines in a Marginal posterior distribution scatterplot I have the following code to draw the scatterplot(s) from an output table; par(mfrow=c(2,2)) plot(temp1[,5], temp1[,6], xlab="log10(r)", ylab="log10(tf)", pch=46) plot(temp2[,5], temp2[,6],

Dear R community, I have a scatterplot with multiple vertical ablines. I wish to color each interval between two ablines in a different color... Could you please indicate me how to do this efficiently? Thank you! Georg. ******************** Georg Ehret Johns Hopkins Baltimore [[alternative HTML version deleted]]

Hello, SAS' point and click interface has the option of produce a scatterplot with a superimposed confidence ellipse for the correlation coefficient. Since I generally like R so much better, I would like to reproduce this in R. I've been playing with the ellipse package. In order to have the points and the ellipse on the same graph I've done the following. (Load ellipse

> On Oct 9, 2017, at 6:03 AM, Big Floppy Dog <bigfloppydog at gmail.com> wrote: > > Hello Ulrik, > > I apologize, but I can not see how to provide a pdf in place of the density > function which calculates a KDE (that is, something from the dataset in the > example). Can you please point to the specific example that might help? > > Here is what I get: > >

Dear R users, I would like to create a filled.contour plot with colour bar and overlay a map. I need to create several of these representing variables with different spatial extents for comparison. When I try to fix the plot area size and axes limits as follows: par(fig=c(0,1.0,0.3125,1.0) filled.contour(x=seq((320/2)-180.5,(480/2)-180.5,len=nrow(oct94)),

Hello Ulrik, I apologize, but I can not see how to provide a pdf in place of the density function which calculates a KDE (that is, something from the dataset in the example). Can you please point to the specific example that might help? Here is what I get: require(mvtnorm) require(ggplot2) set.seed(1234) xx <- data.frame(rmvt(100, df = c(13, 13))) v <- ggplot(faithfuld, aes(waiting,