similar to: Output from while and for loop

Hello, I am having a bit of trouble with scatterplot3d(). I was able to plot a 3d cloud of points using the following code: >my.3dplot<-scatterplot3d(my.coords, pch=19, zlim=c(0,1), scale.y=0.5, angle=30, box=FALSE) where my.coords is a data frame that contains x, y, and z coordinates for grid points whose elevation we sampled. The problem occurs when I try to add points using points3d.

Hello R-help, I am a recent convert to R from SAS and I am having some difficulty with output of a for loop into a matrix. I have searched the help manuals and the archives, but I can't get my code to work. It is probably a syntax error that I am not spotting. I am trying to make a distance matrix by extracting the distances from each point to all others in a vector (the for loop). I can

Hello, I am using a simple linear model and I would like to get an AIC value. I came across both AIC() and extractAIC() and I am not sure which is best to use. I assumed that I should use AIC for a glm and extractAIC() for lm, but if I run my model in glm the AIC value is the same if I use AIC() on an lm object. What might be going on? Did I interpret these functions incorrectly? Thanks,

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 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)

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

I'm completely new at R... I have sinkhole survey data (lat, long, and elevation) and have been trying to plot a rotatable 3d plot for several hours... cannot get it right. Examples I see tend to be grid data (one elevation value per grid cell); however, my data are more random (known elevations at known (but random) x-y positions). Data format is tab separated, i.e.: lat long

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 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

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

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

Hi everyone I have a matrix (let's say that it contains the values of elevation) and want to plot its values on a map using a function such as image.plot or filled.contour. The problem is that my grid is not rectilinear, it is bended. Here is an example lon<-matrix(0,20,25) lat<-matrix(0,20,25) elev<-matrix(0,20,25) for (i in 1:20) { for (j in 1:25) {

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:

# Thanks again to everyone who provided suggestions. # I was curious about which approaches would be the fastest... so a little benchmarking # My approach was by far the worst :) # The approach suggested by Duncan Murdoch and Peter Langfelder, based on indexing , was by far the fastest (~ 66times faster than using nested ifelse() ). All the details can be found below for those who are

Hi there, I am an environmental studies masters student trying to get my thesis out the door. I am also newbie at trees in general, but I like what I see in the literature about the random forest algorithm. I think I get the general gist of things, but even after reading stuff I?m unclear about how I could be getting the results I?m seeing. I obviously am missing something about how the split

Dear R users, I'm trying to determine local population centers in a region through kernel smoothing. What I have is population density in each neighborhood, which can be presented as point density. So in my data set “pop”, I have three columns for about 1000 neighborhoods: x (x coordinate), y (y coordinate), and z (population density at xy). I searched R documentations and found that the

Hello R Users, I am trying to do a quadrat count defined by covariate properties in spatstat. I have read my elevation raster into R (from ascii) and converted to class "im" for use in spatstat. Now I have point data of class "ppp" which window is the same extent as the elevation image. I can conveniently plot the image and the points on the image as follows:

Hello R Users, I am trying to do a quadrat count defined by covariate properties in spatstat. I have read my elevation raster into R (from ascii) and converted to class "im" for use in spatstat. Now I have point data of class "ppp" which window is the same extent as the elevation image. I can conveniently plot the image and the points on the image as follows:

I'm attempting to mount a CIFS share with the following stipulations: 1. I must have the UNIX extensions (specfically, symlinks). 2. I must use plaintext authentication (don't ask). I've recompiled the cifs kernel module to allow plaintext authentication, using the stock Ubuntu 7.10 kernel (2.6.22.9c). My /etc/fstab line looks like... //superman/www-pub

I am sorry if this question is vague or uninformed. I am just learning R and struggling. I am using the book Hierarchical Modeling and Inference in Ecology and they provide examples of R code. I have the following code from the book but when I run it I don't get any output. I cannot get the values of 'out' to show up. Basically, I just want to see my estimates for b0,