similar to: identifying local maxima

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)

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

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, 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 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

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

If a run a LOESS model and then produce a smoothed surface: Is there any way to determine the coordinates of the local maxima on the surface? [[alternative HTML version deleted]]

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:

Hello, I am attempting to get the standard deviation in multiple distance bins in my spatial data. It appears as though the 'variog' command in the geoR package will do the trick, as one of the outputs from 'variog' is 'variog$sd', which, according to the manual, is the "standard deviation of the values in each bin". However, when I run this command, the

# 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

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:

Dear all, I wonder about what could actually be possible with the function "contour": 1/ - the definition of contour lines is most often meaningless when the contours are drawn in areas where no real data points exist. It can however happen that irregular distributions lead to more or less irregular clouds of data points. Interpolations (eg: loess regression, GLM, etc...) are however

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,

Hi all, I was recently writing a script to identify the value and id of the maximum observation in a sliding window when I ran into some unexpected behavior. I have included an example. > test <- c() > test$elev <- c(1:200) > test$i <- 1 > test$window <- 10 The following works for me: > check.max <- function(x){obs.max <- x$elev[x$i:x$i+x$window]; obs.max}