similar to: saving a plot to a file

Hi, I have a set of observations which are divided into two sets A and B. I have some code that bins the dataset into 10 bins based on the max and min of the observed values. I would like to make a histogram of A & B using my calculated bins but plot the distribution of B on top of A (like a stacked barplot). This is possible since both sets A & B are binned using the same bin ranges.

Hello, I have a problem that I think can be solved in R but I'm not sure how to tie things together. I have a digital image of a crystal growth in 2 dimensions. And my aim is to calculate the fractal dimension of the crystal. I was planning to use the box counting method. So I need to read in the image in R (for which I can use the pixmap or rimage packages) and then draw a grid over at a

Hi, is there a way to plot distribution curves (say normal or chi sq etc) from within R? For example I looked up the *chisq family of functions but I'm not sure as to how I would use them to generate a plot of the chi sq distribution (for arbitrary d.o.f). Thanks, ------------------------------------------------------------------- Rajarshi Guha <rajarshi at presidency.com>

Hi, I'm plotting 4 graphs on one page (2x2 matrix) but I cant seem to get the title for the whole page right. I'm doing: op <- par(mfrow = c(2,2), pty="s") hist(var$V2, breaks="FD",main="Euclidean Metric", xlab="Sum of 3NN ... hist(var$V2, breaks="FD",main="Manhattan Metric", xlab="Sum of 3NN ... hist(var$V2,

Hi, I'm using the ks.test() on two vectors. I looked up the reference and also coded up a version of the two sample Smirnov test. My question is that how can I decide from the output of R that the two vectors x & y come from the same distribution? Am I correct in assuming that smaller D values indicate that they come from the same distribution? In addition how can I use the p value that

https://rdrr.io/rforge/fractal/ https://cran.r-project.org/web/packages/fractal/fractal.pdf Hi, I am trying to learn about nonlinear time series, and fractal time series analysis in particular. I am interested in becoming proficient with the 'fractal' package. I have two specific questions: 1. I have a basic understanding of ARMA and ARIMA models. Can someone recommend

Hi, this question is probably very obvious but I just cant see where I might be going wrong. I'm using the lm() function to generate a linear model and then make predictions using a different set of data. To generate the model I do (tdata & pdata are matrices of observations and parameters, tdepv, pdepv are response vectors) x <- as.data.frame(tdata) x$tdepv <- tdepv

Hi all, here's a proposal for a SoC project on wildlife movement patterns analysis. A MSc student is available to anwser the call, of course. The idea has already been briefly discussed with the mantainer of the adehabitat package and the AniMov project community. Short description Develop some add-on functions to use the adehabitat package to perform basic movement ecology analysis, in

Dear R People: At one time, there were packages called fractal and Fractal, respectively, which had different functions. I can't seem to find Fractal any more. Does it still exist somewhere, please? Thanks in advance for any help! Sincerely, Erin -- Erin Hodgess Associate Professor Department of Computer and Mathematical Sciences University of Houston - Downtown mailto: erinm.hodgess

Are there any packages that help with statistical analysis in situations where fractal geometry is relevant? Perhaps something that supports computation of fractal related statistics, such as the Hurst exponent or fractal dimension? Or perhaps which support obvious tasks such as taking samples from a dataset at different levels of granularity (such as sampling spatial data at cm, m, km

R-users: My problem: the package fdim (which measures fractal dimensions of datasets) apparently prefers 3-D (XYZ) datasets. I'm trying to measure the information dimension (a type of fractal dimension) of a 2-D (XY) dataset. Here's some examples of the preferred 3-D data (XYZ): library(fdim) XYZ <- (makehplane(NumN=300, DimM=3, Longit=300)) fdim(XYZ,q=0.999999,PlotF=TRUE)

Hi, I'me trying to write a function that will shuffle a vector. At the moment I'm baically making a vector of randomized indices and then making a new vector from the original one using these random indices. However, is there an alternative (more elegant) method to do this? I tried help.search('shuffle') but it does'nt return anything relevant. Thanks,

Hi all, I started to see fun of gmaps4rails gem from https://github.com/apneadiving/Google-Maps-for-Rails. After everything done. When visited the locahost, i got the following error. undefined local variable or method `acts_as_gmappable'' for #<Class: 0x31a9da8> the error is due to i have line "acts_as_gmappable" in my model. Anybody knows how this is

Greetings of Peace! I am new in R software. I want to use the correlation dimension corrDim in computing a map. I have installed the packages(fractal) in R. Now my problem is this, when I tried your example in the following site http://rgm2.lab.nig.ac.jp/RGM2/func.php?rd_id=fractal:corrDim  > library(fractal) > png(filename="corrDim_%03d_med.png", width=480, height=480) >

Hi, is the following possible - in a given session I make a lot of objects and save when exiting. Usually I note down seperately what each object is about. Is it possible to attach data to any object which would essentially be a short note explaining the meaning of it? Thanks, ------------------------------------------------------------------- Rajarshi Guha <rxg218 at psu.edu>

Hi, I have 3 lists, x, y, z and I'd like to perform a calculation over all the lists simultaneously. If it were a single list I could use lapply, but for more than one list I'm using a for loop. Is there an idiom that would let me use something like lapply, but the function specified to lappy would have access to an element from each list? (In Python, I would have used for a,b,c in

Hi, I have a data.frame that has a categorical variable, for which I would like to look at the distribution of levels of this variable, based on a grouping of two other variables. As an example: x <- data.frame(obs=sample(c('low', 'high'),100, replace=TRUE), grp1=sample(1:10, 100, replace=TRUE), grp2=runif(100)) cut.grp1 <- cut(x$grp1, 3) cut.grp2 <- cut(x$grp2, 3)

Hi, I have a data.frame with columns named X, D1, D2, D3 I know I can get a single plot with 3 curves by doing xyplot(D1 + D2 + D3 ~ X, data) but in some cases I might have columns D1 ... D10. Is there a way to plot all 10 columns without having to specify each individual term? (By analogy with formulae in lm, I thought, xyplot(. ~ X, data) would work, but it didn't) Thanks, --

Hi, I have a factor and I would like to find the most frequent level. I think my current approach is a bit long winded and I was wondering if there was a more elegant way to do it: x <- factor(sample(1:0, 5,replace=TRUE)) levels(x)[ which( as.logical((table(x) == max(table(x)))) == TRUE ) ] (The length of x will always be an odd number, so I wont get a tie in max()) Thanks,

Hi, I have some data which I was plotting using image(). I wanted to add a vertical color key to the plot and I found that heatmap.2 in gplots does let me add a color key. However, I was thinking of a vertical bar with the color range rather than the style that gplots provides. Is there any package (or code snippet) that would let me add a vertical color key to an image() or heatmap