similar to: Spatial Statistics on Grids

I have spatial data on a sphere (the Earth) for which I would like to run an gls model assuming that the errors are autcorrelated, i.e. including a corSpatial correlation in the model specification. In this case the distance metric should be calculated on the sphere, therefore metric = "euclidean" in (for example) corSpher would be incorrect. I would be grateful for help on how to

DeaR comRades: I have a 2D spatial binomial process as shown in the data and code below. I am plotting the number of trials and the number of successes in the spatial binomial experiments and would like to draw the spatial cells were the trials and successes were counted, i.e. a partial grid in the plot only for those cells where there is a number. The cells are 2x2 km cells. The count of Trials

Hi, I am stuck in a looping problem. It might be an easy problem for experienced R users but I have been unable to do it. Any kind of help or advice will be great appreciated. I am creating a spatial grid and have a list of spatial points in a folder. I can read the spatial points separately and get a count of the points in the spatial grid in R. The output should be a table showing the counts of

Dear R users, I am putting together reading and resources lists for spatial statistics and spatial econometrics and am looking for some pointers from more experienced practitioners. In particular, I find two "camps" in spatial modelling, and am wondering which approach is better suitied to which situation. The first camp is along the lines of Venables and Ripley's Chapter 14

Dear Happy R-users & experts, I am in need of advice, While working with spatial data (x & y coordinates of seed locations) I have come accross the problem that I need to convert my point data into a matrix or grid system. I then need to count how often a point falls into a certain position in the matrix or grid. I have searched all day online, asked collegeas but nothing works. Sadly

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

Dear R users, I am currently writing a MCMC algorithm for spatial Poisson model. One problem which I need to solve is as follows: I have a vector X[1:J] which describes characteristics of cells of a rectangular grid. Further, for each cell I have a list of adjascent cells adj[] and the vector listing numbed of adjascent cells num[]. Thus if I want to list cells adjascent to cell i I write

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

I am looking for online courses to learn Spatial Statistics using R. Statistics.com is offering an online course in December on the same topic but that schedule doesn't suit mine. Are there any other similar modes for learning spatial statistics using R??? Can someone please advice??? Thank you. Ravi -- View this message in context:

I?m tryng to use the SPDEP package in my research in the field of population genetics. My data set has the following format: - x and y : coordinates, - Z: allelic frequency in each loci (in a total of 8 locis) - this variable can assume the values 0 ; 0.5 or 1. The objective is to verify if there is a possible spatial autocorrelation structure of the allelic frequency in a population of

Dear all: Does anyone have any suggestions on how to make a spatially explicit landscape with spatial autocorrelation in R? In other words, a landscape where all cells have a spatial reference, and the environment values that are closer in space are more similar (positive spatial autocorrelation). Thank you, Laura

>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

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 Bert, I think you are correct that I can use levelplot, but I have a question about converting data. For example, the statement: levelplot(Z~X*Y), Z is row-wise from the lower left corner to the upper right corner. My dataset just have gridded Z data as a txt file (or can be called matrix?), how to convert them to the vector in order for levelplot to use? Thanks. On Mon, Jan 15, 2018 at 6:04

Dera R helpers, I have a (x,y,z) data file where x and y are spatial coordinates and z a variable. I have some missing values in the z column and I would like to replace them with an optimized estimation from the neighbour cells. I could not find any function in R to do that. Is anybody aware of such function ? Maybe someone knows how to implement the Papadakis method in R... Thanks for your

Sorry for the emails, I just wanted to have an example. layer$z 1 1 3 4 6 2 2 3 4 1 2 9 1 4 5 2 1 8 How to convert the matrix to layer$z = c(1, 4, 5, 2, 1, 8, 2, 3, 4, 1, 2, 9, 1, 1, 3, 4, 6, 2)? I think this vector is the order that levelplot can use. Thanks again. On Mon, Jan 15, 2018 at 10:58 PM, lily li <chocold12 at gmail.com> wrote: > Hi Bert, > > I think

If layer$z is a matrix and you want to reverse the order of the rows, you can do: n <- nrow(layer$z) layer$z <- layer$z[ n:1, ] HTH, Eric On Tue, Jan 16, 2018 at 8:43 AM, lily li <chocold12 at gmail.com> wrote: > Sorry for the emails, I just wanted to have an example. > layer$z > > 1 1 3 4 6 2 > 2 3 4 1 2 9 > 1 4 5 2 1 8 > > How to convert

Hi list, Is there a package that covers the evaluation of spatial statistics on images and not on point data? I've converted an image matrix to x, y coordinates and a measurement value but evaluation with the package spdep (not really designed for image data I suppose) is unworkable. Any suggestions? Regards, Koen

> > Dear R user´s, Is there anyone that may send me *Spatial Statistics* e-book from *Brian Ripley* ? Thanks a lot. Best regards. -- Marcus Vinicius P. de Souza Juiz de Fora - Minas Gerais Brasil [[alternative HTML version deleted]]

Dear R helpers, I'm new to R and struggling with applying functions to a spatial grid data frame, called data for example.data has a variable named "slope" and "uparea" Basically, I need to calculate the tan(data$slope)Next, I need to divide data$uparea by data$slope and take the log() of that all In the basic examples I found how to make simple multiplications with a