Questions tagged [spatial]

The field of study concerning statistical methods that use space and spatial relationships (such as distance, area, volume, length, height, orientation, centrality and/or other spatial characteristics of data) directly in their mathematical computations.

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1answer
24 views

Confidence intervals and uncertainty estimation of classified polygon map

I am not mathematician, neither statistician, but I try to use statistics in my work, so I do my best here to explain the problem I have. I have a map of millions of hectares that consist of nine ...
5
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3answers
5k views

Account for spatial autocorrelation with a binomial regression model

I am using a binomial regression model for presence/absence, with 20 independent variables to test. The data has x and y coordinates and I would like to understand how can I take into account the ...
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1answer
13 views

Lcross Confidence Envelopes - R software

I have performed an Lcross examination in R with the following code: ...
11
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0answers
4k views

Specify correlation structure for different groups in mixed-effects model (lme4/nlme)

I am trying to account for spatial autocorrelation in a linear mixed-effects model in R with measurements repeated in time. BodyMass has been collected once per <...
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0answers
6 views

Moran's eigenvector spatial regression vs autocorrelation term

Comparing two methods for spatial regression: Moran's Eigenvector-based spatial regression Regression with a term for spatial autocorrelation e.g. where $Y = \beta X + \gamma MY + \epsilon$ for ...
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1answer
21 views

What are the possible machine learning models for this geospatial analysis task?

I am new to ML and have some experience with building CNN models. I recently got involved with a research project and here is the task I have to work on: I've been given some (latitudes,longitudes) ...
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1answer
168 views

What is the general idea of Spatial Cox Process?

I can't seem to understand the whole idea of Cox Process in spatial point pattern. Can someone explain it in layman's term? thank you
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0answers
15 views

Hypothesis test for pixel matrix equivalence

I'm going through this tutorial and I'm reworking it in R and I was able to do so. I tried to extend this tutorial by thinking of ways to objectively detect differences in images; e.g., can I run a ...
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0answers
9 views

Spatial modelling: raster calculation from covariate estimates of GLMs produce some negative values in raster distribution data

I am constructing spatial distribution models/maps for soil carbon using coefficient estimates from a GLM. The GLM is made up of a mix of continuous and categorical variables and the response is a ...
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0answers
45 views

Clustering on structural variables?

I'm working with land surface models. These models basically take a bunch of meteorological forcing data (downward radiation, wind, rain, humidity, etc), and run it through some biogeochemical/...
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0answers
66 views

Randomization testing in Bayesian spatial scan statistics

I was reading about Bayesian Spatial Scan statistics paper. I have this confusion about why randomization testing is not necessary in this approach. The paper says that it is by construction. But, I ...
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0answers
85 views

Confusion related to Kulldorff's scan statistics

I was reading this paper related to Bayesian spatial scan statistics where I came across the Kulldorff's scan statistics. I have attached the screenshot of the paper. My objective is to find a ...
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0answers
21 views

Accounting for spatial autocorrelation in model - A simulation

My question, in short, is: I was trying to demonstrate that accounting for spatial autocorrelation reduces the overestimation of significance of a non-autocorrelated fixed effect. The result, ...
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0answers
236 views

how to generate samples with the given autocorrelation function [duplicate]

I want to generate some spatial data where the points/location in the space form a multivariate gaussian distribution. I want these points to have certain autocorrelation given by the variogram model ...
8
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1answer
2k views

Does RandomForest ignore spatial independence?

I have 5 variables for each countries of the world and I need to analyze their effect and interactions on an independent variable. Random Forest would be adequate for my scope as it deals with non-...
7
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2answers
90 views

Spatial Point Process: Does an inhomogeneous first order intensity function affect the second order dependence?

As the title suggests, I am having a bit of confusion on the effect of first order intensity function. If I have a first order intensity function that says in a certain region the points are much more ...
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0answers
10 views

compare a neighbourhood value with the city mean - test of significance in presence of spatial autocorrelation

I have a dataset with all neighbourhoods in a city and a value for each neighbourhood (a rate). I would like to be able to create a vizualization that enables the user to select individual ...
0
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1answer
44 views

compare neighbourhood value with the mean value across all neighbourhoods in the city

I have a dataset with all neighbourhoods in a city and their poverty rates. I would like to be able to create a vizualization that enables the user to select individual neighbourhoods and find out ...
2
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1answer
12 views

How to interpret lines crossing on Ripley's K plot

The image above (which I took from another post) illustrates one of the typical patterns in a K plot. It shows a Ripley's K plot showing the actual below the expected up until a radius of about .17, ...
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3answers
47 views

How to test whether birds spend more time in specific areas along a time-segmented track?

I have geolocation data on birds with 1 position per day (latitude + longitude) plus I have for each day, a corresponding binary time series that takes values 0 or 1. There is periods of minimum 10 ...
0
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1answer
22 views

Empirial Bayes for means

I have data for US ~3100 counties where the variable is a mean score based on a sample. However, for many small counties, the sample size is quite small (like 5), and so these mean values fluctuate a ...
8
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1answer
888 views

Generating data to follow given variogram

It is a straightforward approach having a set of coordinates (e.g., in 2D as {x,y}) and at least an associated variable (e.g., v)...
0
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2answers
16 views

Distance based Spatial sampling

I am struggling with spatial sampling of data which has Latitude & Longitude for data points. I need to do sampling such that no adjacent or nearby point should get selected ( Need to give some ...
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0answers
8 views

why variogram models take only one independent variable

lznr.vgm = variogram(log(zinc)~sqrt(dist), meuse) i am using meuse data for practicing to create variogram models, but i am confused to know there are 14 ...
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0answers
8 views

Given data and covariance matrix in Euclidean space, how to compute covariance matrix in Polar forms without computing the sample covariances?

For 2D, given (x,y) data points, and the covariance matrix C, how to compute the covariance matrix in polar form efficiently without transforming all data to polar form first then compute the sample ...
3
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0answers
196 views

Multiple Imputation for Spatial Models

I'm trying to estimate various spatial models (SAR, SDM, SEM) but have missing data throughout my variables. The mice package in R gives a straightforward solution when none of the variables with a ...
17
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5answers
13k views

2D analog of standard deviation?

Consider the following experiment: a group of people is given a list of cities, and asked to mark the corresponding locations on an (otherwise unlabeled) map of the world. For each city, you will get ...
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0answers
25 views

How to compute measures of dispersion and statistical significance of the impacts of a panel Spatial Durbin model (SDM)?

I ran a panel Spatial Durbin model (SDM) and computed the summary measures of impacts (direct, indirect and total). Now, I would like to get measures of dispersion for the impacts estimates as well as ...
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0answers
5 views

Neighborless regions in hot-spot analysis -GeoDA

I am performing hot-spot analysis on aggregate data in the 632 districts of India. The hot-spot map produced by GeoDA software, using Queen's contiguity weight matrix identifies 5 districts as '...
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0answers
72 views

Bayesian spatial autoregressive (SAR) model with heteroskedasticity in R

In socio-economic data, I always found heteroskedasticity that can't be solved using transformation.I had read a paper "Spatial autoregressive models with unknown heteroskedasticity:A comparison of ...
3
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1answer
2k views

Interpretation of Mantel r correlations

I am using mantel in R package Ecodist to perform a series of partial mantel tests. I am examining the correlation between a species composition (Bray-curtis ...
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0answers
21 views

How to adjust for spatial autocorrelation in panel regression in R

I am running a panel regression with two-way fixed effects, the outcome variable being the number of conflicts in each district each month. My calculation of Moran's I seems to indicate that the ...
1
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0answers
490 views

Estimating a dynamic spatial panel

I am analyzing a spatial panel dataset using the XSMLE package in Stata. My units are a subset of US states (11) and my panel is strongly balanced. The package returns estimations for Main, Spatial, ...
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0answers
15 views

How to best evaluate the quality / precision of geo-spatial prediction?

I have developed an algorithm to predict locations of certain items in 2D-space. The input data consists of various fuzzy / blurred observations of those items. Therefore, I am not performing a binary ...
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0answers
13 views

How to deal with non-stationary spatial autoregressive model

I wonder what to do in case a spatial autoregressive parameter is found to be unity. If in time series econometrics a unit root is detected, differencing the process helps. Is there something similar ...
1
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1answer
32 views

Identifying good areas in a two dimensional graph

I have a an outcome variable with three states: win(green), lose(red) and draw(gray) and a sample of data points, each with a value on two independent variables x and y. I can plot the outcomes using ...
2
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1answer
138 views

Ripley K function value in a specific radius and dataset using R's Kest function

I'm having general trouble with calculating Ripley's K function values. The following is a simple spatial point pattern, where both X and Y range from 0 to 200: Here's its corresponding Ripley K ...
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0answers
37 views

probability involves bivariate gaussian

I'm working on a spatial project. I need to calculate the probability of a point being the closest to another. Say I'm given four points $y$, $x_1$,$x_2$ and $x_3$ in 2D plane, and let $Y'=y+Z$, where ...
0
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1answer
225 views

Spatial prediction on surface: very fine grid vs coarse grid + quick interpolation

Once I have fitted a spatial model (point-referenced data), I need to make a prediction map. A natural approach is to make prediction over a fine grid over the region. However, the required ...
0
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1answer
207 views

Spatstat package and Spatial point process: How to estimate the density when computing the inhomogeneous K-function?

http://www.inside-r.org/packages/cran/spatstat/docs/Kinhom Here we see that to get the inhomogeneous K-function, we can either use a kernel density approximation method with small bandwidth to ...
67
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1answer
7k views

40,000 neuroscience papers might be wrong

I saw this article in the Economist about a seemingly devastating paper [1] casting doubt on "something like 40,000 published [fMRI] studies." The error, they say, is because of "erroneous statistical ...
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0answers
20 views

Comparing 3 raster maps of continuous surface data in R

I have 3 maps representing spatial distribution in hunting pressure. These maps were derived using different methods and I am now interested in comparing them to assess how they might differ/agree ...
0
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1answer
132 views

Clustering spatial data based on location and values

I'm looking for a way, preferably in R, to create a cluster of point data (specifically, the centroids of UK postcodes), where each cluster comes as close as possible to containing a certain number of ...
0
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1answer
253 views

Assessing spatial autocorrelation in structural equation models

I have a SEM built with lavaan and I would like to assess spatial autocorrelation. I found this code written by Jarrett Byrnes that does exactly that: http://www.imachordata.com/space-and-sems-2/ ...
1
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1answer
13 views

Estimating population concentrations in spatially autocorrelated data

I'm stuck on which statistic to use with a spatial data set to resolve population concentrations in a large area, when I have only sampled a small area relative to that large area. Here's an example ...
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0answers
27 views

Inhomogeneous K-function to indicate need for spatial dependence/interaction term in Poisson point process model

I am mapping and modelling a disease of sheep. I have approx 4200 point locations in my dataset, each of which represents the centroid of a given sheep farm. I have created a K-function difference ...
2
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2answers
459 views

How to compare GLS models?

I have spatial data set for 35 studies. In each study, there are variables y, x1, x2, latitude, and longitude. I want to know whether adding x2 to model y~x1 will improve the simple regression model y~...
1
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1answer
44 views

Does standard distance follow the 68-95-99.7 rule?

I'm wanting to do a simple standard distance demonstration for my students in R, but I've come across a conundrum. When I simulate the creation of 10,000 points in a spatial normal distribution, ...
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0answers
7 views

Spatial clustering of ordinal attribute

I have a set of polygons (ESRI shapefile), each with one ordinal value. The values are in the range of 1 to 100. Not all values within this range are used and there can be repetition of values across ...
0
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0answers
38 views

Linear model from iterative process in R

I would like to test a relationship between to factors such as birds occurrence and temperature for instance, to test if temperature affects birds occurrence from a country (e.g. Germany). I have a ...