similar to: RGL package surface plot

Dear R community, I'm having hard time to understand the kde function in "ks" package. Let me use a 3-dimensional kernel smooth example to explain my question using the elevation data in geoR. ### here is what I did ### library(ks) require(geoR) data(elevation) elev.df <- data.frame(x = elevation$coords[,"x"], y = elevation$coords[,"y"], z = elevation$data)

Hello, I am new and am having a hard time getting the proper syntax for output from loops. I am working on a simulation to generate a null expectation of bee behavior. Pieces of it work. The part that I am having specific difficulty is in output of a vector from within the while loop that I am using. Basically the simulation works as such: I have a starting point and a neighbor matrix and a

Dear R users, I have created a Loess surface in R, in which x is relative longitude by miles, y is relative latitude by miles, and z is population density at the neighborhood level. The purpose is to identify some population centers in the region. I'm wondering if there is a way to determine the coordinates (x,y) of each center, so I can know exactly where they are. Let me use the

Dear exports,I have created a hypsometric curve (area-elevation curve) for my watershed by using simple command hypsometric(X,main="Hypsometric Curve", xlab="Relative Area above Elevation, (a/A)", ylab="Relative Elevation, (h/H)", col="blue")It plots the hypsometric curve in "RGraphics window", My question is how can I export values which is used

Hello, I?m using zero-inflated Poisson regression via the zeroinfl() function to analyze data on seed-set of plants, but for some reason, I don?t seem to be getting the output for all three levels of my two categorical predictors. More about my data and model: My response variable is the number of viable seeds (AVInt), and my two categorical predictors are elevation (Elev) and Treatment

Dear list, i'm a new R user, so I apologize if the topic is already being addressed by some other user. I'm trying to determine if the reproductive success of a species of bird is related to a list of covariates. These are the covariates: ? elev: elevation of nest (meters) ? seadist: distance from the sea (meters) ? meanterranova: records of temperature ? minpengS1: records

Dear all, I have built glm models based on presences/absences and a number of predictor maps and would like to compute habitat suitability based on the modelled coefficients. I thought this is pretty straight forward and wanted to use predict() and supply the new data in a data frame, with one column for each predictor. However, I do get an error msg warning me that the number of rows for

Hi users, I have no clear clue about plotting spatial data. For example, I just have a table with attribute values of each grid cell, such as elevation. Then I have coordinates of the upper left corner in UTM, the number of rows and columns, and grid cell size. How to create spatial plot of elevations for the grid cells, in color ramp? Should I create a spatial grid layer with all the polygons

The volume of a polygon = 0. Polyhedra have volumes. This may be irrelevant, but if the lake is cylindrical == constant cross sectional area at all depths, then height doubles when the volume does and vice versa. Otherwise you have to know how area varies with height or use more sensible approximations thereto. Cheers, Bert On Tue, Dec 5, 2023, 20:13 javad bayat <j.bayat194 at

I am new to R and what to find out which package would be best to create a surface plot, 2d or 3d if possible. I have a matrix (depth.dat) which has over 15k depth measurements from an ultrasonic corrosion mapping application. These depth measurements only have one axis (x) but I have used Octave and gnuplot providing decent results, but R seems to have a web interface with PERL which is what I

Thanks Duncan for the replyI can not suppress anything these are radiation pattern measurements that are typically are taken at X,Y and Z planes. See an example here, where I want to plot the measurements for the red, green and blue planes (so the image below withouth the 3d green structure inside)https://www.researchgate.net/publication/258391165/figure/fig7/AS:322947316240401 at

Dear All, I have a question on overlaying a filled.contour (e.g. on soil properties data) and contour (by elevation) in one graph. Both have the same z matrix dimension. I'm able to overlay both graph, but the plots dimension did not overlap well on the same plots. How can I have both filled.contour and contour on the same graph? The commands that I have written are as follows:

You will need to coerce your data into a "spatial" kind, as implemented in `sp` or as of late, `sf` packages. You might want to give the vignettes a whirl before you proceed. Roughly, you will have to coerce the data to Spatial* (you could go for a point, raster or grid type, I think) and also specify the projection. Once you have that, plotting should be handled by packages. Here are a

Thanks. So after searching 4 hours last night it looks like that there is no R package that can do this right now. Any other ideas or suggestions might be helpful.RegardsAlex On Wednesday, June 21, 2017 3:21 PM, Alaios via R-help <r-help at r-project.org> wrote: Thanks Duncan for the replyI can not suppress anything these are radiation pattern measurements that are typically are

Hi Roman, Thanks for your reply. For the spatial coordinates layer, I just have coordinates of the upper left corner, numbers of rows and columns of the spatial map, and grid cell size. How to create a spatial layer of coordinates from this data? Thanks. On Mon, Jan 15, 2018 at 3:26 PM, Roman Lu?trik <roman.lustrik at gmail.com> wrote: > You will need to coerce your data into a

Hi, I am working with a SpatialPolygonsDataFrame of many islands. There are a lot of polygons (islands) composing my SpatialPolygonsDataFrame. I want to extract the elevation of each island. I need to separate the different polygons (like dissolve function in arcgis), to have the elevation of each island. Do you have any idea how can I do that ? I already read a lot of forum, and read the

Hi there, I have two data sets, one of locations at different elevations (x,y,z) and the other of points that make up topographic contours (also x,y,z). I have used: result<-apply(distppll(data2,cbind(topocon[-nrow(topocon),],topocon[-1,])),1,min) where 'data2' are my measurement coordinates (x, y) and 'topocon' are my topographic contours (x,y). While this gives me an output

Is there packaged code to convert geographical coordinates (e.g., longitude, latitude, elevation) to Cartesian coordinates in 3-space? I can see how to do this using 1. a spherical-to-Cartesian conversion like pracma::sph2cart(tpr) http://cran.r-project.org/web/packages/pracma/ 2. a geographical-to-spherical conversion. This seems to involve (in roughly increasing order of difficulty or

1. I'm attempting to test for Random Effects. I've grouped the data on subject (grid) but want to use lme to build the model without subject as a RE then add it and do anova between the 2 models. This is the result I get and it appears it's adding Random Effects. tmp.dat4 <- groupedData(Trials ~ 1 | grid, data = tmp.dat4) mod2a <- lme(Trials ~ factor(group_id) + reversal,

>From your description, I am **guessing** that you may not want a "spatial map" (including projections) at all, but rather something like a level plot. See ?levelplot in the lattice package for details. Both I am sure ggplot2 has something similar. Apologies if I havemisunderstood your intent/specifications. Cheers, Bert Bert Gunter "The trouble with having an open mind is