similar to: placing labels in polygon center ?

Hello, I need to calculate the centroids of some spatial polygons that I have placed into a Polygons-class object. Is the labeling point in the Polygons-class the centroid of the polygon? Thank you for your help.

Hi everyone, i've been trying to make a special plot with ggplot2, but I can't get it to fill the polygon I'd like to see filled so very very much. I want to display the difference or change in the distribution of the modified Rankin Scale between two groups. mRS is a scale for disability or daily activities competence. It looks like this.

Hello all, I am wondering if there is a way to do a spatial error probit/logit model in R? I can't seem to find it in any of the packages. I can do it in MATLAB with Gibbs sampling, but would like to confirm the results. Ideally I would like to use this model to predict probability of parcel conversion in a future time period. This seems especially difficult in a binary outcome model

I am searching for a utility in R which will determine the mean location of a closed contour and eventually record the location in an ASCII file. By means of the contour utility in R, I am able to produce an image of a contour, but I am seeking a procedure which will produce the coordinates of the center of mass of the contour. From my actual set of data, the contour utility will produce several

I have obtained shapefiles for Indian states from here: http://www.maptell.com/index.php?option=com_remository&Itemid=159&func=fileinfo&filecatid=115&parent=category Problem: I want to extract centroid coordinates for each State, but there is some coding problem with the shapefiles that prevents this. #Code: #After extracting the shapefiles from the india_state.zip file, then:

Dear stats experts: Me and my little brain must be missing something regarding bootstrapping. I understand how to get a 95%CI and how to hypothesis test using bootstrapping (e.g., reject or not the null). However, I'd also like to get a p-value from it, and to me this seems simple, but it seems no-one does what I would like to do to get a p-value, which suggests I'm not understanding

Hi all, I need a little help for construct an state's map on R. The first problem is to get the data. I have a datafile of longitude and latitude in the follow format: trajectory latitude longtude T -22.045618 -51.287056 T -22.067078 -51.265888 T -22.067039 -51.207249 T -22.059690 -48.089695 T -22.075529 -48.074608 T -22.072460 -48.044472 T -22.062767 -48.298473 T -22.077349

If anyone has a very fast vectorized method for doing the following I would appreciate some help. I want to avoid outer() to limit memory problems for very large n. Let x = real vector of length n y = real vector of length n w = real vector of length m, m typically less than n/2 but can be > n z = real vector of length m For w[i], i=1,,,m, find the value of x that is closest to w[i]. In

hello all, I'm overlaying numerous scatter plots onto a map (done in PBSmodelling). In this case I'm placing each plot by setting par(fig) to the centroid of map polygons. The location/mapping part is not so important. There are cases of small overlaps for some plots (ie figures) so I'm keen to write or find a function that moves my small scatter plots so they don't overlap. A

Dear R User, Please, I am new to R. I want to overlay density plot for predictive interval pooled result in meta-analysis. http://addictedtor.free.fr/graphiques/graphcode.php?graph=114 Regards Frank Peter

I am modeling a trend surface using trmat and want to trim the resulting matrix to the area enclosed by my real data (i.e., remove all the extrapolated areas). I was using chull and in.chull to calculate the convex hull and change all the other values created by trmat to NA. However, my real data has portions that are slightly concave so chull would give me slivers that are extrapolations from

Dear R-users Idea: Plot a dnorm line using specific mean/sd to complete a histogram (skewed). xs:range of y-values, ys: dnorm function Problem: I expected to multiply the ys function with the sample size (n=250-300). I was wondering about a factor between 12'000 and 30'000 to match the size of the dnorm line with the specific histogram. Thanks Sibylle hist(Biotree[Ld,]$Height2008,

What is the simplest (namely: minimum number of libraries or conflicts) way to fill a polygon with a pattern? For example, suppose I have (in a graphic file, like a jpeg) the drawing of an "X". Then I fill a polygon (like a triangle) with this pattern, and get something like: X XXX XXXXX XXXXXXX (where the border "X"s could be truncated). I searched the rimage

Hi everyone, I have coding for repeating pentagon as below: plot(0:11,type="n") for (i in 1:10 )polygon(rep(c(4,5,7,8,6)), i*c(.5,.3,.3,.5,.7), bor=2) which are increasing vertically. Now, I want to know how to rotate the pentagon, so that I will get pattern like flower. Basicly, repeating pentagon in circle. Thanks alot for helping me to solve this problem. -- Hemavathi

Hi, I have a plot with type="o", or overstruck. Now I am trying to add the legend, but I couldn't figure out how to show the overstruck type in the legend. It seems that the legend only allows one to set lty. Does anyone know how to show overstruck in the legend? Thanks! -- Tom [[alternative HTML version deleted]]

Hello: I'm dealing with an issue currently that I'm not sure the best way to approach. I've got a very large (10G+) dataset that I'm trying to create a histogram for. I don't seem to be able to use hist directly as I can not create an R vector of size greater than 2.2G. I considered condensing the data previous to loading it into R and just plotting the frequencies as a

Here's some code to make lissajous dance. I've attached a small sample GIF. Cheers, Rob Steele robsteele at yahoo dot com plot.lissajous = function(omega.x, omega.y, delta = 0, num.thetas = 200) { thetas = seq(0, 2 * pi, length = num.thetas) xs = sin(omega.x * thetas + delta) ys = cos(omega.y * thetas) plot(xs, ys, type = 'l', lwd = 3, ann = FALSE, axes = FALSE) }

Hi, It is most probably just my R-ignorance, but I have following problem with using predict(). I train the model using 164 cases and then I try to use it on the data set with 35 cases, but I am getting 164 predictions ? R-code below illustrates in more detail what I am doing. Truly yours, R train = read.csv("train.csv", header = TRUE, row.names = "mol",

Dear R-List users, Can anyone explain exactly the difference between Weights options in lm glm and gls? I try the following codes, but the results are different. > lm1 Call: lm(formula = y ~ x) Coefficients: (Intercept) x 0.1183 7.3075 > lm2 Call: lm(formula = y ~ x, weights = W) Coefficients: (Intercept) x 0.04193 7.30660 > lm3 Call:

I've written a simple function to draw a regression line in a plot and annotate the line showing the slope with a label. It works, as I'm using it, when the horizontal variable is 'x', but gives incorrect results otherwise. What's wrong? # simple function to show the slope of a line show.beta <- function(model, x="x", x1, x2, label, col="black", ...)