search for: elevation

...ctor 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 certain threshold distance for travel. In the while loop the "bee" moves to a randomly chosen neighbor location. I want to be able to record the elevations of these points (including the starting point) so that I can look at variance in elevation and mean elevation. The loop itself works as does the calculation of the final elevation list, change in elevation list, and true total distance traveled. I have looked in all of the email archives but hav...

...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 "elevation" data set in geoR to illustrate what have done: require(geoR) data(elevation) elev.df <- data.frame(x = 50 * elevation$coords[,"x"], y = 50 * elevation$coords[,"y"], z = 10 * elevation$data) elev.loess <- loess(z ~ x * y, data = elev.df, degree = 2, span = 0.1) g...

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) H<-Hpi(elev.df) elev.smt<-kde(elev.df,H=H) plot(elev.smt, drawpoints=TRUE) If I unders...

...ve 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 "kde" function in the "ks" package might be the one I'm looking for. To illustrate what I have done, I use the elevation data in GeoR: ##### Kernel smooth #### require(geoR) data(elevation) elev.df <- data.frame(x = 50 * elevation$coords[,"x"], y = 50 * elevation$coords[,"y"], z = 10 * elevation$data) H<-Hpi(elev.df) popcnt<-kde(elev.df,H=H) plot(popcnt, axes=TRUE, box=TRUE, drawpo...

I would like to plot a map of, say, California, showing the elevation areas. I am sure there must be a source where I can find the dataset for the elevation and maybe there's an implementation in R that allows me to map it. Any ideas would be highly appreciated. -- View this message in context: http://r.789695.n4.nabble.com/elevation-map-with-R-tp4641116.html...

...), representing the location that samples were collected. Population <- gl( n=6, k=5,length=120, labels =c("CO", "CN","Ga","KO", "Mw", "Ng")) # You would like to assign a particular value to each level of population (in this case the elevation at which they were collected). In a vectorized approach (for speed... pretend this was a big data set..) elevation <- ifelse(Population=="CO", 2169, ifelse(Population=="CN", 1121, ifelse(Population=="Ga", 500, ifelse(Population=="KO", 2500, i...

Dear Rusers, I am now using R and SAS to fit the piecewise linear functions, and what surprised me is that they have a great differrent result. See below. #R code--Knots for distance are 16.13 and 24, respectively, and Knots for y are -0.4357 and -0.3202 m.glm<-glm(mark~x+poly(elevation,2)+bs(distance,degree=1,knots=c(16.13,24)) +bs(y,degree=1,knots=c(-0.4357,-0.3202 )),family=binomial(logit),data=point) summary(m.glm) Coefficients: Estimate Std. Error z value Pr(>|z|) (Intercept)...

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: >plot(elevation, axes=T, col=ter...

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: >plot(elevation, axes=T, col=ter...

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 of temperature ? wchillpengS1: records of temperature ? minpengS2: records of temperature ? wchillpengS2: records of temperature ? nnd: nearest neighbour dist...

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...

...or O(1)? # I have one additional question. I would have guessed that initializing an empty vector of the right size would have sped up the subsequent operation, filling that vector, but it does not seem to have much of an effect. Any thoughts? # i.e. using N <- 6000000 # number of observations elevation <- rep(NA, length(Population)) # This does not really speed things up much. ##### Population <- gl( n=6, k=5,length=N, labels =c("Ga", "CO", "CN","KO", "Ng", "Mw")) # You would like to assign a particular value to each level of...

Hi, First, thanks for all people that continuously giving great advice on this list! I am setting up a standalone server (Debian 10, Samba 4.9.5+dfsg-5 from Debian). The following directory is shared and contains two directories: /home/eleve/partage/ ??? Documents ??? Travail I want user "eleve" to be able to modify everything, and guest users to have read access on

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...

...by creating a new class, that would be preferable. I've also attached a more detailed sample of data. Thanks, Chris Dolanc -- Christopher R. Dolanc Post-doctoral Researcher University of Montana and UC-Davis -------------- next part -------------- Data Plot Lat LatCat Elevation ElevCat Type SizeClass Stems Area Density 5171 VTM 39C16 39.76282 Lat6 1500 Elev1 Conifer Class3 0 751.5347 0.00000 5172 VTM 39C16 39.76282 Lat6 1500 Elev1 Conifer Class4 1 751.5347 13.30611 5771 VTM 39F11 39.57721 Lat6...

...size:612.0pt 792.0pt; margin:72.0pt 72.0pt 72.0pt 72.0pt; mso-header-margin:36.0pt; mso-footer-margin:36.0pt; mso-paper-source:0;}div.WordSection1 {page:WordSection1;}-->Hello,Iam trying to take the information from the summary of my best fit logisticregression model for the occurrence of a high elevation plant spp. and createthe appropriate equation that will calculate probability of occurrence, given thedata. My predictors include both continuous variables (slope and a second orderpolynomial of elevation) and a discrete variable for aspect (warm and cool). Ihave left unchanged the default contrast...

...oinfl() 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 (Treatment). Elev has three levels: 01-Low, 02-Mid, and 03-High; Treatment also has three possibilities: B, F, or O. Because the response variable (AVInt) is zero-inflated and Poisson-distributed, I?m using zeroinfl() under the pcsl library as an alternative to factorial ANO...

Dear all; I have a dataframe with several columns. The columns are the elevation, volume and the area of the cells (which were placed inside a polygon). I have extracted them from DEM raster to calculate the volume under polygon and the elevation for a specific volume of the reservoir. > head(x6,2) Elevation Vol Area V_sum A_sum 1 2145 13990.38 85.8...

Hi all, I'm working to apply a function that will generate a matrix of results only when a specific criteria is met. I want my final results to be a matrix with both the values that meet the criteria (the results of the function), and those that to do in the same positions in the matrix (the original numbers). Here's a sample of what I would like to do: t.mean.1.c <- c(-15, -20,

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,