similar to: how to identify the value in a scatterplot?

Is there any way to make the points on my scatterplot matrix correspond to numbers instead of dots? I know how to do this on a regular 2-variable scatterplot but not on the matrix. Thanks! -Lydia [[alternative HTML version deleted]]

Hello everybody, I'm trying to understand how to draw a smoothed scatterplot on a geographic map with R. Have a dataframe with point locations (long, lat) and was able to simply plot these points on a shp map by using the maptools package. However, instead of having simply the raw points on the map, I would like to have a "smoothed" scatterplot of the same superimposed on the map.

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).

Hi. I would like to make a scatterplot where all of the points are evenly spaced from each other - however, they are all the same size and occupy the entire graph. For example: x = rep(c(1:10), 10) y = rep(c(10:1), each = 10) plot(x, y, pch = 0) Gives me a scatter plot with 100 square points each evenly spaced between each other. But these points don't fill up the entire space and if I try

Hi everyone, is there a way/package in R that would allow me to select a group of points from a scatterplot by drawing a circle around them or some such? I can use 'identify' to pick individual points, but that gets tedious if one has more than 10-20 spots. I can easily select spots within a rectangle defined by picking points using identify... but a simple rectangle sometimes will

Do I recall correctly that there is an R package that can take an image, and help one estimate the x/y coordinates? I can't find the package, thought it was an R-tool, but would appreciate any leads. Thanks, Rob

Hello everyone, This is just a quick double check. It concerns the 'scatterplot function' in R. I have 6 curves and I wish to represent each of them by a different kind of line (their colour must be black). The curves are derived from the cuminc function...the coordinates of which are in 'xx'. Upon reading the documentation in R, it looks like I can use the 'on/off'

Dear all, How can I label/unlabel points on scatterplot with mouse pointer. As the mouse approches near to point, it should label the closest point, then unlabel when it moves away. How can I do in R? I be very thankful. Thanks and Regards, Hitesh Singla -- This message has been scanned for viruses and dangerous content by MailScanner, and is believed to be clean.

Hi All- I have 24 boxplots on one graph. I do not have the whiskers extending to the outliers, but I would like to label the maximum value of each outlier above the whiskers. I have the stats but am having trouble figuring out how to label the whiskers. Any suggestions would be great! sherri

Hello all, I wrote a small function to add labels for outliers in a boxplot. This function will only work on a simple boxplot/formula command (e.g: something like boxplot(y~x)). Code + example follows in this e-mail. I'd be happy for any suggestions on how to improve this code, for example: - Handle boxplot.matrix (which shouldn't be too hard to do) - Handle cases of complex

R plotting experts: I have a bivariate dataset composed of 300 (x,y) continuous datapoints. 297 of these points are located within the y range of [0,10], while 2 are located at 20 and one at 55. No coding errors, real outliers. When plotting these data with a scatterplot, I obviously have a problem. If I plot the full dataset with ylim = c(0,55), then I cannot see the structure in the data in

Hello, I'm new in this R world and I don't know much about statistics, but now I have to analize some data and I've got some first queries yet: I have 5 sets of area mesures and each set has 5 repetitions. My first step is to check data looking for outliers. I've used the outliers package. I have to use the cochran test and the grubbs test in case I find any outlier. The problem

I have a process where I am creating a effects plot similar to the cowles effect example. I would like to add the point estimates to the effects plot, can someone show me the correct syntax. I have included the "R" effects example, so you can show me the correct syntax. Thanks mod.cowles <- glm(volunteer ~ sex + neuroticism*extraversion, data=Cowles, family=binomial)

I've got a data frame with 23 columns, and wanted to plot a scatterplot matrix of it. I called pairs( df ) where 'df' is my data frame. This did generate the matrix, but the plotting window did not expand to make the individual plots large enough to see. Each one was only about 10 pixels high and wide. I tried sending the plot to a file, with a high and wide image, by doing

Hi, I am trying to use function pairs to plot the scatterplot, but I only want to keep the upper triangle, what's the argument to do this? Thanks, -Jack [[alternative HTML version deleted]]

Dear all, I have two sets of data (say set1 and set2) as follow: set1 x1 x2 x3 0.30 0.43 3.88 0.38 0.59 3.53 0.30 0.42 2.12 0.33 0.53 2.12 0.30 0.47 3.76 set2 y1 y2 y3 0.32 0.47 5.18 0.23 0.26 1.06 0.42 0.65 3.88 0.28 0.38 3.76 0.35 0.47 1.41 The "pairs" function (such as pairs(~x1+x2+x3 data=set1, main="Simple Scatterplot Matrix") ) is

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.

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Hello dear R help list, I wish to compile a check-list for diagnostic measures for OLS regression. My question: Can you offer more (or newer) tests/measures for the validity of a linear model then what is given here: http://www.statmethods.net/stats/rdiagnostics.html This resource gives a list of measures to test for: OUTLIERS, INFLUENTIAL OBSERVATIONS, NON-NORMALITY, NON-CONSTANT ERROR

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