similar to: require(dataset) for example.

Hello all, I am using the clustering functions in R in order to work with large masses of binary time series data, however the clustering functions do not seem able to fit this size of practical problem. Library 'hclust' is good (though it may be sub par for this size of problem, thus doubly poor for this application) in that I do not want to make assumptions about the number of

Sincerely, Jeffrey Todd Lins Executive Director Quantitative Analysis Saxo Bank A/S (Sent from my BlackBerry) ----- Original Message ----- From: r-sig-finance-bounces at stat.math.ethz.ch <r-sig-finance-bounces at stat.math.ethz.ch> To: r-help <R-help at stat.math.ethz.ch>; r-sig-finance at stat.math.ethz.ch <r-sig-finance at stat.math.ethz.ch> Sent: Wed Apr 02 06:49:54 2008

Dear All, I was searching through the spatstat manual in order to find a function to simulate a Poisson pattern only within a fixed radius (circular moving window) around individual points. If points are distributed heterogeneously over a large area this may help to only assess deviation from CSR within the window and thus does not require additional information on a covariate. I could not find

Hello, I have fitted a Poisson Process model in spatstat using >fit1<-ppm(points, ~elevation, covariates=list(elevation=elevation.im)) This far, everything went well, but I try to simulate the fitted model using the function: >sim1<-rmh(fit1) But I get the error message: "Extracting model information...Evaluating trend...done. Checking arguments..determining simulation

Dear R-users, I would like to show you a simple example that gives an overview of one of my current issue. Although my working setting implies a different parametric model (which cannot be framed in the glm), I guess that what I'll get from the following example it would help for the next steps. Anyway here it is. Firstly I simulated from a series of exposures, a series of deaths (given a

I normally use the following code to create a figure displaying the mark correlation function for the point pattern process "A": M<-markcorr(A) plot(M) I have now started to use the following code to perform 1000 Monte Carlo simulations of Complete Spatial Randomness (CSR). It is a Monte Carlo test based on envelopes of the Mark correlation function obtained from simulated point

Hello everyone, My data consists of marked points and several covariates, whereby the marks are the time points of the observations. The problem is, that one of the covariates is hard to handle as an image. This covariate represents the type of roads. As there aren't roads at every location of the map, one cannot specify the value of the covariate at any point on a grid, which is necessary to

A new version 1.9-5 of the package `spatstat' has been uploaded to CRAN. What it is: ---------- spatstat is a package for analysing spatial data, mainly Spatial Point Patterns. What's in it: ------------ Functions for exploratory data analysis, model-fitting, simulation, spatial sampling, model diagnostics, and formal inference. Data types include point patterns, line segment patterns,

A new version 1.9-5 of the package `spatstat' has been uploaded to CRAN. What it is: ---------- spatstat is a package for analysing spatial data, mainly Spatial Point Patterns. What's in it: ------------ Functions for exploratory data analysis, model-fitting, simulation, spatial sampling, model diagnostics, and formal inference. Data types include point patterns, line segment patterns,

I'm looking into the help page on some functions of the {spatstat} packages and they're exemplified by a dataset called "nztrees". But it does not exist, and it's not listed on R Datasets Package (http://stat.ethz.ch.sixxs.org/R-manual/R-devel/library/datasets/html/00Index.html). Why is this happening.... -- View this message in context:

Dear all, I'm working with two point patterns (ppp) in spatstat. I turned one of them into a spatial covariate (im) object. After that, I used this im object to fit a Poisson model for the second point pattern, using the covariate layer from the first one. In R, the whole thing looks somewhat like this: my_first.im <- as.im(my_first.ppp) test.ppm <- ppm (my_second.ppp, ~my_first,

Hi I'm trying to run an admb model from R by using the system () command. The admb model runs fine when running it from the admb command line or when using emacs. However when I try it with system() then R crashes every time. And I tried using the R command line and RGui and in both it crashes. I also tried it from different computers. What I do is I first set the directory where I keep

Dear R users I have been looking for functions that can deal with overdispersed poisson models. According to actuarial literature (England & Verall, Stochastic Claims Reserving in General Insurance , Institute of Actiuaries 2002) this can be handled through the use of quasi likelihoods instead of normal likelihoods. However, we see them frequently in this type of data, and we would like to

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Dear Rusers, I'd like to take the cases of cancer of the larynx in chorley(spatstat) to explain my question. I want to join the points of cancer of the larynx with the disused industrial incinerator to generate lines, and then calculate the angles of these line comparing the horizontal line? How can i get it? It seems to be difficult to get the angles Thanks a lot. -- With Kind

I am trying to determine how to evaluate homogeneity of points in three-dimensional space. In two-dimensional data, I have used functions available in the Spatial package and I've have looked into the spatstat package but, as far as I can tell, neither appears to handle 3-dimensional data. Is there another version, package, or software that does the same type (G-function,

Dear R users I have been looking for functions that can deal with overdispersed poisson models. Some (one) of the observations are negative. According to actuarial literature (England & Verall, Stochastic Claims Reserving in General Insurance , Institute of Actiuaries 2002) this can be handled through the use of quasi likelihoods instead of normal likelihoods. The presence of negatives is not

Ranjan Maitra writes: > Does anyone have a suggestion (or better still) code for sampling > from the uniform distribution over the convex hull of a set of > points? This is implemented in library 'spatstat'. If x and y are vectors of coordinates of your initial set of points, library(spatstat) W <- convexhull.xy(x, y) P <- runifpoint(42, W) will compute

Dear list, I posted essentially this same question to the r-sig-geo mailing list last week with no response :( Unfortunately I am no closer to reaching a solution, so I now post it here (with some clarifications) in the hope that someone following this list might have an answer for me: Has anyone had much experience with spatial interaction (or gravity) models, specifically in the form of

I upgraded to R version 2.6.0 yesterday; now I find that I can't load spatstat. I re-installed spatstat (that part seemed to work without complaint) but when I execute > library(spatstat) I get the error message Error in dyn.load(file, ...) : unable to load shared library '/Users/rturner/Rlib/spatstat/libs/ i386/spatstat.so':