similar to: How to draw partial grid in plot for spatial-binomial experiment?

Dear all, I am trying to project my LongLat-maps to a plane. The ultimate purpose is to do a search of points in vicinity of other points using overlay-commands (sp) with radius in km. I am applying spTransform (package rgdal) and it gives my some curious results. An example. Let's take a point lying somewhere in Germany, zone=32U x <- 8.968735 y <- 49.454735 After conversion I

Dear, I am trying to visualise a time-progressing line (it's supposed to represent spread patterns) using brew package and Google Earth. The idea is to have a function which takes start and end point geographic coordinates, as well as number of intervals to chop the path up, and returns the collection of points segmenting this line. Unfortunately my calculations fail for large distances,

Dear All, I need to convert some Northing-Easting coordinates from the Gauss-Krüger system into latitude-longitude. Any suggestions on how to do it? Regards, Marco Marco Giannitrapani Statistical Consultant Tel: +44151373 5945 Email: Internet: http://www.shell.com [[alternative HTML version deleted]]

On 21/10/2020 8:45 a.m., Balint Radics wrote: > Hello, > > Could someone suggest a package/way to make a 3D raster plot of the Earth > (with continent boundaries), and then make a "cut" or "slice" of it such > that one can also visualize some scalar quantity as a function of the > Radius/Depth across that given slice ? > > Formally, I would have a

Hello friends of R, My name is Toni, i'm 25 and I'm working on the Meteorological Investigation team from Balearic Islands. I had contact to you because I have a problem: I done a file for every day since 1912 about precipitation. That file has the following structure: > str(Ast) Loading required package: sp Formal class 'SpatialPixelsDataFrame' [package "sp"]

SUMMARY: Specific problem: I'm regridding biomass-burning emissions from a global/unprojected inventory to a regional projection (LCC over North America). I need to have boundaries for Canada, Mexico, and US (including US states), but also Caribbean and Atlantic nations (notably the Bahamas). I would also like to add Canadian provinces and Mexican states. How to put these together? General

I've enconuntered this problem with the last cran version of geoR: > library(geoR) > day <- rep(1:2, each=5) > coords <- matrix(rep(runif(10),2), 10, 2) > data <- rnorm(10) > data[1] <- NA > as.geodata(cbind(coords, data, day), realisations=4) as.geodata: 1 points removed due to NA in the data Errore in as.geodata(cbind(coords, data, day), realisations = 4) :

Hello fellow R-users,   I’m stuck with something i think is pretty stupid, but i can’t find out where i’m wrong, and it’s turning me crazy!   I am doing a very simple linear regression with Northing/Easting data, then I plot the data as well as the regression line :   > plot(x=Dataset$EASTING, y=Dataset$NORTHING) > fit <- lm(formula = NORTHING ~ EASTING, data = Dataset) > abline(fit)

ComRades: I am geeting the error message Error in ldots[[which(MET)]] : attempt to select less than one element when I try to fit the geostatistical model with the likfit() function of geoR. I have tried with old data for which likfit() successfully maximised the likelihood in previous versions of geoR, and yet the current version fails. I have tried in Windows Vista and Windows XP (I haven't

Dear all, I am looking for a clustering method usefull to classify the countries in some clusters taking account of: a) the geographical distance (in km) between countries and b) of some macroeconomic indicators (gdp, life expectancy...). Are there some packages in R usefull for this? Thanks a lot for your help, Dorina

I have nc files for global soil moisture,here is one file https://echange-fichiers.inra.fr/get?k=f9DDllPKdUKs5ZNQwfq from the metadata ,the projection is cylindrical and the resolution is 25 km(it is based on authalic sphere based on International 1924 ellipsoid).As I want to compare with other data, I have to make them identical. - my other data are in WGS84 with 0.25*0.25 degree resolution

summary: I can display a lon-lat map on a lattice::layerplot, and I can display a Lambert conformal conic (LCC) map on a spam::image, but I can't display an LCC map on a lattice::layerplot. Example follows. What am I doing wrong? details: I've been using `lattice` (via `rasterVis`) successfully to display global atmospheric data, which works well enough (though I am definitely intrigued

Hi, I'm a new R user. My goal is to do a variogram using geoR. I started by trying to do the example in the geoR Illustrative Session using my own data. I am able to read in my Ascii data using: D <- matrix(scan("file.dat", n=530*3), 530,3, byrow=TRUE). Then I use: as.geodata(D, coords.col=1:2, data.col=3) to make the object D geodata. I check the descriptive statistics,

Hi everyone, I wonder if anyone knows the reason why the outputs of the same reprojection in r and arcgis are different?. The magnitude of the change can be up to 40 km in the poles. Basically, I have a database of points equally separated by one degree over the globe. In ARCGIS, I am projecting the data in GCS-WGS-1984 and then reprojected it to Berhmann to ensure equal area

I'm having trouble getting fun="cloglog" to work with plot on a survfit object. Here are the data I used for the commands that follow. days status 2 0 2 0 5 1 9 0 14 1 16 0 16 0 17 0 29 1 30 0 37 1 37 0 39 1 44 0 44 0 58 0 60 1 67 1 68 1 82 1 82 1 86 0 86 0 89 1 93 0 97 1 100 0 100 0 100 0 > library(survival) Loading required package: splines > eg1.km <-

Greetings I'm using R 2.8 with recent (last month) versions of the packages I need to use at present. I'm interested in examining hierarchical spatio-temporal patterns in a data set. The data consist of 94 points (X, Y, UTM coordinates) at which catch rates for a fish were recorded and there are also estimates of prey available for these fish at the same locations.

Dear colleagues I found duplicate coordinates trying to convert a dataframe object (see the attached file) into a geodata one ('geoR' package is needed). My dataframe object consists of 2 columns with UTM geographical coordinates and a 3rd column with fish densities . To overcome the handicap I must add a tiny value generated by rnorm() to each geographical coordinate. And it must be in

Hi all, I use kriging to interpolate the precipitation from stations, but the map of this results show lots of stripes. (please see the attachment)I think there's something wrong with the setting of the dimension of this matrix, however, I have no idea how to know or test to see if this setting is correct or not.I've tried to switch the latitude and longitude, but still got the same

*Apologies if this is not the right way to ask a question, I'm a first timer posting here. Does anyone have a solution to this? I'm having trouble figuring out how to use weighting with K Means Clustering. So say if my dataset is: Column 1 = x coords Column 2 = y coords Column 3 = frequency each coordinate occurs So I'm basically trying to weight the points more heavily if

I've been trying to get some code to run on a 64-bit FreeBSD machine running R : Copyright 2006, The R Foundation for Statistical Computing Version 2.3.0 (2006-04-24) ISBN 3-900051-07-0 and keep getting a core dump with the following results: *** caught segfault *** address 0x0, cause 'unknown' Traceback: 1: .Call("R_point_in_polygon_sp", as.numeric(point.x),